CN112287926A - Method, device and equipment for correcting graphic questions - Google Patents
Method, device and equipment for correcting graphic questions Download PDFInfo
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Abstract
The specification discloses a correction method of graphic topics, which comprises the following steps: acquiring a graph of a subject to be corrected and response content corresponding to the subject to be corrected in a target area; presetting the graph of the to-be-corrected topic to obtain a first feature vector; according to the first feature vector, determining a correct answer of the question to be corrected in a database; and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question. The invention obtains the first characteristic vector by processing the graph of the subject to be corrected, and then determines the correct answer of the subject to be corrected according to the first characteristic vector, thereby judging whether the answering content corresponding to the subject to be corrected is correct or not, solving the problem that the subject to be corrected is difficult to accurately identify due to less graph subjects and characters in the prior art, and ensuring that the graph subjects are more accurate when corrected.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method, an apparatus, and a device for correcting a graphic title.
Background
At present, students are more and more homework, which brings considerable workload for instructors to modify homework, and the instructors need to modify the topics of a large number of homework besides handling busy work.
The existing method for correcting the task of the job mainly depends on matching the corresponding task in the question bank by the text content, and correcting the task according to the matching result. If the existing method is applied to correct graphic topics with few characters, most effective information of the graphic topics is contained in the graphics, only a few general sentences without resolution are contained in the question stem, and the few characters are difficult to accurately identify the topics to be corrected, so that correction of operation is influenced.
Disclosure of Invention
The specification provides a method, a device and equipment for correcting graphic questions, and solves the problem that in the prior art, the questions to be corrected are difficult to accurately identify due to the fact that the number of graphic questions and characters is small.
To solve the above technical problem, the present specification is implemented as follows:
the method for correcting the graphic title provided by the specification comprises the following steps:
acquiring a graph of a subject to be corrected and response content corresponding to the subject to be corrected in a target area;
presetting the graph of the to-be-corrected topic to obtain a first feature vector;
according to the first feature vector, determining a correct answer of the question to be corrected in a database;
and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
Optionally, the obtaining of the graph of the to-be-corrected question and the response content corresponding to the to-be-corrected question in the target area specifically includes:
positioning a subject area in the target area according to the first identification characteristic, and acquiring a graph of the subject to be corrected in the subject area;
and positioning a response area in the target area according to the second identification characteristic, and acquiring response content corresponding to the to-be-corrected question in the response area.
Optionally, the first identification feature is a print script feature or a print shape feature.
Optionally, the second identification feature is a handwriting feature.
Optionally, the obtaining a first feature vector by performing a preset process on the graph of the to-be-corrected topic specifically includes:
processing the graph of the to-be-corrected topic by an image vectorization model to obtain a second feature vector;
and combining the second characteristic vector with the text content of the subject to be corrected to obtain the first characteristic vector.
Optionally, the image vectorization model includes a convolutional neural network.
Optionally, the database includes an index database and a content database;
the determining, according to the first feature vector, a correct answer to the to-be-corrected question in a database specifically includes:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be corrected according to the feature vector with the highest similarity;
and searching the standard answer of the subject to be corrected in the content database according to the subject number corresponding to the subject to be corrected.
Optionally, when the fault tolerance in the answers is determined, the correct answers of the questions to be corrected are displayed.
The present specification provides a device for correcting a graphic topic, the device includes:
the acquisition unit is used for acquiring the graph of the question to be corrected and the answering content corresponding to the question to be corrected in the target area;
the processing unit is used for carrying out preset processing on the graph of the to-be-corrected topic to obtain a first feature vector;
the determining unit is used for determining the correct answer of the to-be-corrected question in a database according to the first feature vector; and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
Optionally, the obtaining unit is specifically configured to:
positioning a subject area in the target area according to the first identification characteristic, and acquiring a graph of the subject to be corrected in the subject area;
and positioning a response area in the target area according to the second identification characteristic, and acquiring response content corresponding to the to-be-corrected question in the response area.
Optionally, the first identification feature is a print script feature or a print shape feature.
Optionally, the second identification feature is a handwriting feature.
Optionally, the processing unit is specifically configured to:
processing the graph of the to-be-corrected topic by an image vectorization model to obtain a second feature vector;
and combining the second characteristic vector with the text content of the subject to be corrected to obtain the first characteristic vector.
Optionally, the image vectorization model includes a convolutional neural network.
Optionally, the database includes an index database and a content database;
the determining unit is specifically configured to:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be corrected according to the feature vector with the highest similarity;
and searching the standard answer of the subject to be corrected in the content database according to the subject number corresponding to the subject to be corrected.
Optionally, when the fault tolerance in the answers is determined, the correct answers of the questions to be corrected are displayed.
The present specification provides a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to perform the steps of:
acquiring a graph of a subject to be corrected and response content corresponding to the subject to be corrected in a target area;
presetting the graph of the to-be-corrected topic to obtain a first feature vector;
according to the first feature vector, determining a correct answer of the question to be corrected in a database;
and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
The present specification provides a graphic topic correction device comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the device to perform the following:
the acquisition unit is used for acquiring the graph of the question to be corrected and the answering content corresponding to the question to be corrected in the target area;
the processing unit is used for carrying out preset processing on the graph of the to-be-corrected topic to obtain a first feature vector;
the determining unit is used for determining the correct answer of the to-be-corrected question in a database according to the first feature vector; and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:
the invention obtains the first characteristic vector by processing the graph of the subject to be corrected, and then determines the correct answer of the subject to be corrected according to the first characteristic vector, thereby judging whether the answering content corresponding to the subject to be corrected is correct or not, solving the problem that the subject to be corrected is difficult to accurately identify due to less graph subjects and characters in the prior art, and ensuring that the graph subjects are more accurate when corrected.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the specification, and for those skilled in the art, other drawings can be derived based on the drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a method for correcting a graphic topic provided in an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a device for correcting a graphic topic provided in the second embodiment of the present specification.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present disclosure without making any creative effort, shall fall within the protection scope of the present disclosure.
Fig. 1 is a schematic flow chart of a method for modifying a graphic topic according to an embodiment of the present disclosure, where the schematic flow chart includes:
step S101, obtaining the graph of the subject to be corrected and the answering content corresponding to the subject to be corrected in the target area.
In step S101 in the embodiment of this specification, acquiring a graphic of a title to be changed in a target area specifically includes the following steps: positioning a question area in a target area according to a first identification characteristic, and acquiring a picture of a question to be corrected in a question area, wherein the first identification characteristic is a printing handwriting characteristic or a printing shape characteristic, the target area can be a certain question to be corrected, the area containing the printing handwriting characteristic or the printing shape characteristic is determined as the question area, and the picture of the question to be corrected is acquired in the question area; or, the target area can also be a whole test paper to be corrected, successively positions areas containing the printing handwriting characteristics or the printing shape characteristics, determines the areas containing the printing handwriting characteristics or the printing shape characteristics as the subject areas, and respectively obtains the graphs of the subjects to be corrected in the subject areas.
In step S101 in the embodiment of the present specification, the step of obtaining the answering content corresponding to the to-be-modified title in the target area may specifically include the following steps: and positioning a response area in the target area according to the second identification characteristic, and acquiring response content corresponding to the to-be-corrected question in the response area, wherein the second identification characteristic is a handwriting characteristic. The handwriting characteristics and the printing characteristics or the printing shape characteristics can be identified through a pre-trained neural network model, and the handwriting and the printing are easily identified when in identification because the handwriting is not very standard.
Step S102, the graph of the to-be-corrected topic is subjected to preset processing to obtain a first feature vector.
In step S101 in the embodiment of this specification, the graph of the to-be-corrected topic is subjected to a preset process to obtain a first feature vector, and the specific steps may be as follows:
processing the graph of the to-be-corrected topic by an image vectorization model to obtain a second feature vector, wherein the image vectorization model comprises a convolutional neural network;
and combining the second characteristic vector with the text content of the subject to be corrected to obtain the first characteristic vector.
And S103, determining the correct answer of the to-be-corrected question in a database according to the first feature vector.
In step S103 of the embodiment of the present specification, the database includes an index database and a content database, and the database may be applied in an offline state.
In step S103 in the embodiment of this specification, determining a correct answer to the to-be-corrected question in a database according to the first feature vector may specifically include the following steps:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be corrected according to the feature vector with the highest similarity; and searching the standard answer of the subject to be corrected in the content database according to the subject number corresponding to the subject to be corrected. The index database and the content database are linked by using a unique title number, wherein: the content database comprises information of the content, answers, knowledge point analysis and the like of all graphic questions; the index database comprises first characteristic vectors of all graphic topics, and the first characteristic vectors can be formed by combining the characteristic vectors extracted by the image vectorization model and the text contents of the topics.
And step S104, determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
In step S104 in the embodiment of the present specification, when the correct answer of the to-be-corrected question is consistent with the answering content, it is determined that the answering content of the current to-be-corrected question is correct; and when the correct answer of the to-be-corrected question is inconsistent with the answering content, determining that the answering content of the current correction question is wrong. When the fault tolerance in the answer is determined, displaying the correct answer, the detailed analysis content and the like of the question to be corrected, displaying the correction result and the user answer area in a graph uploaded by the user, and simultaneously listing the detailed standard answer, the question analysis content and the like.
In step S104 of the embodiment of the present specification, when the assistant modifies the student homework, when it is determined that the fault tolerance exists in the answer, the correct answer of the question to be modified is displayed, so as to improve the efficiency of modifying the graphic question by the assistant, and in addition, the assistant can be helped to know the reason why the student wrongly responds to the question, so as to help the assistant effectively assist the student; when the students correct the graphic questions by themselves, when the fault tolerance in the answers is determined, the detailed contents of correct answers, analysis and the like of the questions to be corrected are displayed, effective help is provided for the students to correct the faults, and the efficiency of the students to correct the questions by themselves is improved.
In the method for modifying a graphic topic provided in the above embodiment, a user may photograph the graphic topic through an image acquisition device, and finally obtain a solution of the graphic topic and high-quality knowledge point analysis, and know whether the topic is answered correctly or not. Wherein the image acquisition device may be a camera.
With the development of the internet and communication technology, obtaining the picture questions by photographing and carrying out the batch improvement of the picture questions and obtaining the reference answers of the questions and the analysis of knowledge points become a favorable means for improving the learning efficiency and the tutoring quality. The embodiment breaks through the technical bottleneck that the graphic subjects are difficult to modify in the prior art, provides a complete solution for modifying the graphic subjects, enables the answers and high-quality knowledge point analysis of the graphic subjects to be better transmitted to users, and better realizes fair education.
The invention obtains the first characteristic vector by processing the graph of the subject to be corrected, and then determines the correct answer of the subject to be corrected according to the first characteristic vector, thereby judging whether the answering content corresponding to the subject to be corrected is correct or not, solving the problem that the subject to be corrected is difficult to accurately identify due to less graph subjects and characters in the prior art, and ensuring that the graph subjects are more accurate when corrected.
Fig. 2 is a schematic structural diagram of a modifying apparatus for graphic subjects provided in the second embodiment of the present specification, the schematic structural diagram including: the device comprises an acquisition unit 1, a processing unit 2 and a determination unit 3.
The obtaining unit 1 is used for obtaining the graph of the subject to be corrected and the answering content corresponding to the subject to be corrected in the target area.
The processing unit 2 is configured to perform preset processing on the graph of the to-be-corrected topic to obtain a first feature vector.
The determining unit 3 is configured to determine, according to the first feature vector, a correct answer to the question to be corrected in a database; and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
The obtaining unit 1 is specifically configured to:
positioning a subject area in the target area according to the first identification characteristic, and acquiring a graph of the subject to be corrected in the subject area;
and positioning a response area in the target area according to the second identification characteristic, and acquiring response content corresponding to the to-be-corrected question in the response area.
The first identification feature is a printed writing feature or a printed shape feature.
The second identification feature is a handwriting feature.
The processing unit 2 is specifically configured to:
processing the graph of the to-be-corrected topic by an image vectorization model to obtain a second feature vector;
and combining the second characteristic vector with the text content of the subject to be corrected to obtain the first characteristic vector.
The image vectorization model includes a convolutional neural network.
The database comprises an index database and a content database;
the determining unit 3 is specifically configured to:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be corrected according to the feature vector with the highest similarity;
and searching the standard answer of the subject to be corrected in the content database according to the subject number corresponding to the subject to be corrected.
And when the fault tolerance in the answers is determined, displaying the correct answers of the questions to be corrected.
The invention obtains the first characteristic vector by processing the graph of the subject to be corrected, and then determines the correct answer of the subject to be corrected according to the first characteristic vector, thereby judging whether the answering content corresponding to the subject to be corrected is correct or not, solving the problem that the subject to be corrected is difficult to accurately identify due to less graph subjects and characters in the prior art, and ensuring that the graph subjects are more accurate when corrected.
The present specification provides a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to perform the steps of:
acquiring a graph of a subject to be corrected and response content corresponding to the subject to be corrected in a target area;
presetting the graph of the to-be-corrected topic to obtain a first feature vector;
according to the first feature vector, determining a correct answer of the question to be corrected in a database;
and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
The present specification provides a graphic topic correction device comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the device to perform the following:
the acquisition unit is used for acquiring the graph of the question to be corrected and the answering content corresponding to the question to be corrected in the target area;
the processing unit is used for carrying out preset processing on the graph of the to-be-corrected topic to obtain a first feature vector;
the determining unit is used for determining the correct answer of the to-be-corrected question in a database according to the first feature vector; and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing an integrated circuit chip, such programming is mostly implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific programming Language, which is called Hardware Description Language (HDL), and the HDL is not only one but many, and it should be clear to those skilled in the art that the Hardware circuit for implementing the logic method flow can be easily obtained by only slightly programming the logic of the method flow in the above Hardware Description languages and programming the integrated circuit.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for correcting a graphic topic, the method comprising:
acquiring a graph of a subject to be corrected and response content corresponding to the subject to be corrected in a target area;
presetting the graph of the to-be-corrected topic to obtain a first feature vector;
according to the first feature vector, determining a correct answer of the question to be corrected in a database;
and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
2. The method for correcting graphic questions according to claim 1, wherein the obtaining of the graphic of the question to be corrected and the response content corresponding to the question to be corrected in the target area specifically comprises:
positioning a subject area in the target area according to the first identification characteristic, and acquiring a graph of the subject to be corrected in the subject area;
and positioning a response area in the target area according to the second identification characteristic, and acquiring response content corresponding to the to-be-corrected question in the response area.
3. The method of claim 2, wherein the first identification feature is a printed writing feature or a printed shape feature.
4. The method of claim 2, wherein the second identification feature is a handwriting feature.
5. The method for correcting a graphic topic according to claim 1, wherein the obtaining a first feature vector by subjecting the graphic of the topic to be corrected to a preset process specifically comprises:
processing the graph of the to-be-corrected topic by an image vectorization model to obtain a second feature vector;
and combining the second characteristic vector with the text content of the subject to be corrected to obtain the first characteristic vector.
6. The method of modifying a graphical subject of claim 5, wherein the image vectorization model comprises a convolutional neural network.
7. The method of modifying graphic subjects according to claim 1, wherein said database comprises an index database and a content database;
the determining, according to the first feature vector, a correct answer to the to-be-corrected question in a database specifically includes:
matching the first feature vector with the feature vector of the index database to obtain a feature vector with the highest similarity, and determining the question number corresponding to the question to be corrected according to the feature vector with the highest similarity;
and searching the standard answer of the subject to be corrected in the content database according to the subject number corresponding to the subject to be corrected.
8. The method of claim 1, wherein when the error tolerance in the response is determined, a correct answer to the subject to be corrected is displayed.
9. An apparatus for modifying a graphic title, the apparatus comprising:
the acquisition unit is used for acquiring the graph of the question to be corrected and the answering content corresponding to the question to be corrected in the target area;
the processing unit is used for carrying out preset processing on the graph of the to-be-corrected topic to obtain a first feature vector;
the determining unit is used for determining the correct answer of the to-be-corrected question in a database according to the first feature vector; and determining whether the answering content is correct or not according to the correct answer of the to-be-corrected question.
10. An apparatus for modifying a graphical topic, the apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the apparatus of claim 9.
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| CN201910666726.1A CN112287926A (en) | 2019-07-23 | 2019-07-23 | Method, device and equipment for correcting graphic questions |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113033721A (en) * | 2021-05-31 | 2021-06-25 | 北京世纪好未来教育科技有限公司 | Title correction method and computer storage medium |
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| CN115841670A (en) * | 2023-02-13 | 2023-03-24 | 福建鹿鸣教育科技有限公司 | Operation error question collecting system based on image recognition |
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