CN113128558B - 基于浅层空间特征融合与自适应通道筛选的目标检测方法 - Google Patents
基于浅层空间特征融合与自适应通道筛选的目标检测方法 Download PDFInfo
- Publication number
- CN113128558B CN113128558B CN202110266707.7A CN202110266707A CN113128558B CN 113128558 B CN113128558 B CN 113128558B CN 202110266707 A CN202110266707 A CN 202110266707A CN 113128558 B CN113128558 B CN 113128558B
- Authority
- CN
- China
- Prior art keywords
- feature fusion
- target detection
- loss function
- target
- adaptive channel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 49
- 230000004927 fusion Effects 0.000 title claims abstract description 47
- 238000012216 screening Methods 0.000 title claims abstract description 29
- 230000003044 adaptive effect Effects 0.000 title claims abstract description 25
- 238000012549 training Methods 0.000 claims abstract description 24
- 238000013527 convolutional neural network Methods 0.000 claims abstract description 17
- 238000012795 verification Methods 0.000 claims abstract description 14
- 238000013135 deep learning Methods 0.000 claims abstract description 5
- 230000006870 function Effects 0.000 claims description 44
- 239000013598 vector Substances 0.000 claims description 25
- 238000000034 method Methods 0.000 claims description 13
- 238000011176 pooling Methods 0.000 claims description 12
- 230000004913 activation Effects 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 8
- 238000005070 sampling Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 claims description 2
- 239000012855 volatile organic compound Substances 0.000 claims description 2
- 238000000605 extraction Methods 0.000 abstract 1
- 238000011160 research Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/253—Fusion techniques of extracted features
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/07—Target detection
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Computational Linguistics (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Image Analysis (AREA)
Abstract
Description
Claims (5)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110266707.7A CN113128558B (zh) | 2021-03-11 | 2021-03-11 | 基于浅层空间特征融合与自适应通道筛选的目标检测方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110266707.7A CN113128558B (zh) | 2021-03-11 | 2021-03-11 | 基于浅层空间特征融合与自适应通道筛选的目标检测方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113128558A CN113128558A (zh) | 2021-07-16 |
CN113128558B true CN113128558B (zh) | 2022-07-19 |
Family
ID=76772942
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110266707.7A Active CN113128558B (zh) | 2021-03-11 | 2021-03-11 | 基于浅层空间特征融合与自适应通道筛选的目标检测方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113128558B (zh) |
Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113537397B (zh) * | 2021-08-11 | 2024-04-19 | 大连海事大学 | 基于多尺度特征融合的目标检测与图像清晰联合学习方法 |
CN113822265A (zh) * | 2021-08-20 | 2021-12-21 | 北京工业大学 | 一种基于深度学习的x光安检图像中非金属打火机检测方法 |
CN113807231B (zh) * | 2021-09-14 | 2024-02-13 | 西安电子科技大学 | 基于unet下采样卷积神经网络的x光违禁物检测方法 |
CN113763381A (zh) * | 2021-09-28 | 2021-12-07 | 北京工业大学 | 一种融合图像全局信息的对象检测方法及*** |
CN114078230B (zh) * | 2021-11-19 | 2023-08-25 | 西南交通大学 | 一种自适应特征融合冗余优化的小目标检测方法 |
CN114186641B (zh) * | 2021-12-16 | 2022-08-09 | 长安大学 | 一种基于深度学习的滑坡易发性评价方法 |
CN116503406B (zh) * | 2023-06-28 | 2023-09-19 | 中铁水利信息科技有限公司 | 基于大数据的水利工程信息管理*** |
CN117115723B (zh) * | 2023-10-23 | 2024-01-23 | 四川泓宝润业工程技术有限公司 | 一种消防设施计数方法、装置、存储介质及电子设备 |
CN117830788B (zh) * | 2024-03-06 | 2024-05-10 | 潍坊科技学院 | 一种多源信息融合的图像目标检测方法 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105844653A (zh) * | 2016-04-18 | 2016-08-10 | 深圳先进技术研究院 | 一种多层卷积神经网络优化***及方法 |
CN108647668A (zh) * | 2018-05-21 | 2018-10-12 | 北京亮亮视野科技有限公司 | 多尺度轻量级人脸检测模型的构建方法及基于该模型的人脸检测方法 |
US10223611B1 (en) * | 2018-03-08 | 2019-03-05 | Capital One Services, Llc | Object detection using image classification models |
CN110852974A (zh) * | 2019-11-12 | 2020-02-28 | 网易(杭州)网络有限公司 | 图像抗锯齿处理方法、图像生成器的训练方法及装置 |
CN112348823A (zh) * | 2020-09-22 | 2021-02-09 | 陕西土豆数据科技有限公司 | 一种面向对象的高分辨率遥感影像分割算法 |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DK177154B1 (da) * | 2010-12-17 | 2012-03-05 | Concurrent Vision Aps | Method and device for parallel processing of images |
CN108108807B (zh) * | 2017-12-29 | 2020-06-02 | 北京达佳互联信息技术有限公司 | 学习型图像处理方法、***及服务器 |
CN108510012B (zh) * | 2018-05-04 | 2022-04-01 | 四川大学 | 一种基于多尺度特征图的目标快速检测方法 |
EP3830793A4 (en) * | 2018-07-30 | 2022-05-11 | Memorial Sloan Kettering Cancer Center | MULTIMODE, MULTI-RESOLUTION DEEP LEARNING NETWORKS FOR SEGMENTATION, OUTCOME PREDICTION, AND MONITORING LONGITUDINAL RESPONSES TO IMMUNOTHERAPY AND RADIATION THERAPY |
CN112330716B (zh) * | 2020-11-11 | 2022-08-19 | 南京邮电大学 | 一种基于可抑制异常的时空通道约束相关滤波跟踪方法 |
-
2021
- 2021-03-11 CN CN202110266707.7A patent/CN113128558B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105844653A (zh) * | 2016-04-18 | 2016-08-10 | 深圳先进技术研究院 | 一种多层卷积神经网络优化***及方法 |
US10223611B1 (en) * | 2018-03-08 | 2019-03-05 | Capital One Services, Llc | Object detection using image classification models |
CN108647668A (zh) * | 2018-05-21 | 2018-10-12 | 北京亮亮视野科技有限公司 | 多尺度轻量级人脸检测模型的构建方法及基于该模型的人脸检测方法 |
CN110852974A (zh) * | 2019-11-12 | 2020-02-28 | 网易(杭州)网络有限公司 | 图像抗锯齿处理方法、图像生成器的训练方法及装置 |
CN112348823A (zh) * | 2020-09-22 | 2021-02-09 | 陕西土豆数据科技有限公司 | 一种面向对象的高分辨率遥感影像分割算法 |
Non-Patent Citations (1)
Title |
---|
Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning;Ştefan Săftescu等;《2020 IEEE International Conference on Robotics and Automation (ICRA)》;20200915;第4358-4363页 * |
Also Published As
Publication number | Publication date |
---|---|
CN113128558A (zh) | 2021-07-16 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113128558B (zh) | 基于浅层空间特征融合与自适应通道筛选的目标检测方法 | |
CN109584248B (zh) | 基于特征融合和稠密连接网络的红外面目标实例分割方法 | |
CN108647585B (zh) | 一种基于多尺度循环注意力网络的交通标识符检测方法 | |
CN109543502B (zh) | 一种基于深度多尺度神经网络的语义分割方法 | |
CN112396002A (zh) | 一种基于SE-YOLOv3的轻量级遥感目标检测方法 | |
CN112990116B (zh) | 基于多注意力机制融合的行为识别装置、方法和存储介质 | |
CN111882031A (zh) | 一种神经网络蒸馏方法及装置 | |
CN113378938B (zh) | 一种基于边Transformer图神经网络的小样本图像分类方法及*** | |
CN115631344B (zh) | 一种基于特征自适应聚合的目标检测方法 | |
CN116310850B (zh) | 基于改进型RetinaNet的遥感图像目标检测方法 | |
CN112232355A (zh) | 图像分割网络处理、图像分割方法、装置和计算机设备 | |
CN112257727A (zh) | 一种基于深度学习自适应可变形卷积的特征图像提取方法 | |
CN116863194A (zh) | 一种足溃疡图像分类方法、***、设备及介质 | |
CN112084897A (zh) | 一种gs-ssd的交通大场景车辆目标快速检测方法 | |
CN111899203A (zh) | 基于标注图在无监督训练下的真实图像生成方法及存储介质 | |
CN111368634A (zh) | 基于神经网络的人头检测方法、***及存储介质 | |
CN114511785A (zh) | 基于瓶颈注意力模块的遥感图像云检测方法及*** | |
CN117710841A (zh) | 一种无人机航拍图像的小目标检测方法、装置 | |
CN117011515A (zh) | 基于注意力机制的交互式图像分割模型及其分割方法 | |
CN116452900A (zh) | 一种基于轻量级神经网络的目标检测方法 | |
Rao et al. | Roads detection of aerial image with FCN-CRF model | |
CN117011219A (zh) | 物品质量检测方法、装置、设备、存储介质和程序产品 | |
CN110826726B (zh) | 目标处理方法、目标处理装置、目标处理设备及介质 | |
CN117152542B (zh) | 一种基于轻量化网络的图像分类方法和*** | |
Tan et al. | Thermal Infrared Human Recognition Based on Multi-scale Monogenic Signal Representation and Deep Learning |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right | ||
TR01 | Transfer of patent right |
Effective date of registration: 20231007 Address after: Building 5, Guohua Times Square, No. 29666 Youyou Road, Shizhong District, Jinan City, Shandong Province, 250002 Patentee after: Shandong Future Group Co.,Ltd. Address before: 522000, No. 107, Building G, Dongyi District, Xiaocui Road, Xinhe Community, Dongsheng Street, Rongcheng District, Jieyang City, Guangdong Province Patentee before: Jieyang Chengyu Intellectual Property Service Co.,Ltd. Effective date of registration: 20231007 Address after: 522000, No. 107, Building G, Dongyi District, Xiaocui Road, Xinhe Community, Dongsheng Street, Rongcheng District, Jieyang City, Guangdong Province Patentee after: Jieyang Chengyu Intellectual Property Service Co.,Ltd. Address before: 400065 Chongwen Road, Nanshan Street, Nanan District, Chongqing Patentee before: CHONGQING University OF POSTS AND TELECOMMUNICATIONS |