7.1.7.7.1 YOLO, You Only Look Once, Family Object Detection

Chapter Contents (Back)
Object Detction. YOLO.

Srivastava, G.[Gargi], Srivastava, R.[Rajeev],
User-interactive salient object detection using YOLOv2, lazy snapping, and gabor filters,
MVA(31), No. 3, March 2020, pp. Article17.
WWW Link. 2004
BibRef

Kim, M.[Munhyeong], Jeong, J.[Jongmin], Kim, S.[Sungho],
ECAP-YOLO: Efficient Channel Attention Pyramid YOLO for Small Object Detection in Aerial Image,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Hui, T.[Tian], Xu, Y.L.[Yue-Lei], Jarhinbek, R.[Rasol],
Detail texture detection based on YOLOV4-tiny combined with attention mechanism and bicubic interpolation,
IET-IPR(15), No. 12, 2021, pp. 2736-2748.
DOI Link 2109
BibRef

Amudhan, A.N., Sudheer, A.P.,
Lightweight and computationally faster Hypermetropic Convolutional Neural Network for small size object detection,
IVC(119), 2022, pp. 104396.
Elsevier DOI 2202
Small-size object detection, Real-time, YOLO, Robotic vision, Faster RCNN, Light-weight models BibRef

Wang, G.B.[Guan-Bo], Ding, H.W.[Hong-Wei], Li, B.[Bo], Nie, R.C.[Ren-Can], Zhao, Y.F.[Yi-Fan],
Trident-YOLO: Improving the precision and speed of mobile device object detection,
IET-IPR(16), No. 1, 2022, pp. 145-157.
DOI Link 2112
BibRef

Xing, Z.Q.[Zhi-Qiang], Chen, X.[Xi], Pang, F.Q.[Feng-Qian],
DD-YOLO: An object detection method combining knowledge distillation and Differentiable Architecture Search,
IET-CV(16), No. 5, 2022, pp. 418-430.
DOI Link 2207
DARTS, high-efficiency detection, knowledge distillation, YOLOv4 BibRef

Wang, L.[Lili], Ni, Q.H.[Qing-Hang], Chen, C.[Chen], Yang, H.[Hailu],
Lightweight target detection algorithm based on improved YOLOv4,
IET-IPR(16), No. 14, 2022, pp. 3805-3813.
DOI Link 2212
BibRef

Li, X.A.[Xi-Ang], Deng, J.Y.[Jing-Yu], Fang, Y.[Yi],
Few-Shot Object Detection on Remote Sensing Images,
GeoRS(60), 2022, pp. 1-14.
IEEE DOI 2112
Object detection, Feature extraction, Remote sensing, Proposals, Learning systems, Computer architecture, Training, You-Only-Look-Once (YOLO) BibRef

Wang, G.B.[Guan-Bo], Ding, H.W.[Hong-Wei], Yang, Z.J.[Zhi-Jun], Li, B.[Bo], Wang, Y.H.[Yi-Hao], Bao, L.Y.[Li-Yong],
TRC-YOLO: A real-time detection method for lightweight targets based on mobile devices,
IET-CV(16), No. 2, 2022, pp. 126-142.
DOI Link 2202
CBAM, dilated convolution, object detection, receptive field block (RFB), TridentNet, YOLO BibRef

Qu, Z.[Zhong], Gao, L.Y.[Le-Yuan], Wang, S.Y.[Sheng-Ye], Yin, H.N.[Hao-Nan], Yi, T.M.[Tu-Ming],
An improved YOLOv5 method for large objects detection with multi-scale feature cross-layer fusion network,
IVC(125), 2022, pp. 104518.
Elsevier DOI 2208
Object detection, Feature extraction, Feature fusion, , Autoanchor mechanism BibRef

Qu, Z.[Zhong], Shang, X.[Xue], Xia, S.F.[Shu-Fang], Yi, T.M.[Tu-Ming], Zhou, D.Y.[Dong-Yang],
A method of single-shot target detection with multi-scale feature fusion and feature enhancement,
IET-IPR(16), No. 6, 2022, pp. 1752-1763.
DOI Link 2204
BibRef

Tian, D.X.[Da-Xin], Lin, C.M.[Chun-Mian], Zhou, J.S.[Jian-Shan], Duan, X.T.[Xu-Ting], Cao, Y.[Yue], Zhao, D.Z.[De-Zong], Cao, D.[Dongpu],
SA-YOLOv3: An Efficient and Accurate Object Detector Using Self-Attention Mechanism for Autonomous Driving,
ITS(23), No. 5, May 2022, pp. 4099-4110.
IEEE DOI 2205
Detectors, Feature extraction, Object detection, Convolution, Computer architecture, Autonomous vehicles, Visualization, intelligent transportation systems BibRef

Lan, Y.[Yubin], Lin, S.M.[Shao-Ming], Du, H.[Hewen], Guo, Y.Q.[Ya-Qi], Deng, X.L.[Xiao-Ling],
Real-Time UAV Patrol Technology in Orchard Based on the Swin-T YOLOX Lightweight Model,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Xia, R.Y.[Rui-Yang], Li, G.Q.[Guo-Quan], Huang, Z.W.[Zheng-Wen], Meng, H.Y.[Hong-Ying], Pang, Y.[Yu],
Bi-path Combination YOLO for Real-time Few-shot Object Detection,
PRL(165), 2023, pp. 91-97.
Elsevier DOI 2301
Few-shot object detection, Transfer learning, Real-time, Bi-path Combination, You Only Look Once, Attentive DropBlock BibRef

Zhao, Z.P.[Zuo-Peng], He, C.[Chen], Zhao, G.M.[Guang-Ming], Zhou, J.[Jie], Hao, K.[Kai],
RA-YOLOX: Re-parameterization align decoupled head and novel label assignment scheme based on YOLOX,
PR(140), 2023, pp. 109579.
Elsevier DOI
WWW Link. 2305
Object detection, YOLO series, Decoupled head, Label assignment BibRef

Wan, D.H.[Da-Hang], Lu, R.S.[Rong-Sheng], Wang, S.L.[Sai-Lei], Shen, S.Y.[Si-Yuan], Xu, T.[Ting], Lang, X.L.[Xian-Li],
YOLO-HR: Improved YOLOv5 for Object Detection in High-Resolution Optical Remote Sensing Images,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Wang, M.[Min], Yang, W.Z.[Wen-Zhong], Wang, L.[Liejun], Chen, D.[Danny], Wei, F.Y.[Fu-Yuan], KeZiErBieKe, H.[HaiLaTi], Liao, Y.Y.[Yuan-Yuan],
FE-YOLOv5: Feature enhancement network based on YOLOv5 for small object detection,
JVCIR(90), 2023, pp. 103752.
Elsevier DOI 2301
Small object detection, Feature enhancement, Spatial-aware BibRef

Zhao, Q.[Qi], Liu, B.[Binghao], Lyu, S.C.[Shu-Chang], Wang, C.L.[Chun-Lei], Zhang, H.[Hong],
TPH-YOLOv5++: Boosting Object Detection on Drone-Captured Scenarios with Cross-Layer Asymmetric Transformer,
RS(15), No. 6, 2023, pp. 1687.
DOI Link 2304
BibRef

Mahaur, B.[Bharat], Mishra, K.K.,
Small-object detection based on YOLOv5 in autonomous driving systems,
PRL(168), 2023, pp. 115-122.
Elsevier DOI 2304
Architectural changes, Deep learning, Autonomous driving, Small object detection, YOLOv5 BibRef

Hnewa, M.[Mazin], Radha, H.[Hayder],
Integrated Multiscale Domain Adaptive YOLO,
IP(32), 2023, pp. 1857-1867.
IEEE DOI 2303
BibRef
Earlier:
Multiscale Domain Adaptive YOLO for Cross-Domain Object Detection,
ICIP21(3323-3327)
IEEE DOI 2201
Detectors, Feature extraction, Object detection, Training, Adaptive systems, Proposals, Object detection, domain adaptation, multiscale. Training, Instruments, Feature extraction, Real-time systems, Domain shift BibRef

Li, W.S.[Wei-Sheng], Huang, L.[Lin],
YOLOSA: Object detection based on 2D local feature superimposed self-attention,
PRL(168), 2023, pp. 86-92.
Elsevier DOI 2304
BibRef

Bacea, D.S.[Dan-Sebastian], Oniga, F.[Florin],
Single stage architecture for improved accuracy real-time object detection on mobile devices,
IVC(130), 2023, pp. 104613.
Elsevier DOI 2301
Deep learning, Convolutional neural networks, Lightweight object detectors, YOLO, Mobile devices BibRef

Jiang, Y.[Yue], Li, W.J.[Wen-Jing], Zhang, J.[Jun], Li, F.[Fang], Wu, Z.C.[Zhong-Cheng],
YOLOv4-dense: A smaller and faster YOLOv4 for real-time edge-device based object detection in traffic scene,
IET-IPR(17), No. 2, 2023, pp. 570-580.
DOI Link 2302
BibRef

Cheng, Y.[Yong], Wang, W.[Wei], Zhang, W.J.[Wen-Jie], Yang, L.[Ling], Wang, J.[Jun], Ni, H.[Huan], Guan, T.Z.[Ting-Zhao], He, J.X.[Jia-Xin], Gu, Y.K.[Ya-Kang], Tran, N.N.[Ngoc Nguyen],
A Multi-Feature Fusion and Attention Network for Multi-Scale Object Detection in Remote Sensing Images,
RS(15), No. 8, 2023, pp. 2096.
DOI Link 2305
BibRef

Huo, L.[Lina], Hou, J.Y.[Jia-Yue], Feng, J.[Jie], Wang, W.[Wei], Liu, J.S.[Jin-Sheng],
Global and Multiscale Aggregate Network for Saliency Object Detection in Optical Remote Sensing Images,
RS(16), No. 4, 2024, pp. 624.
DOI Link 2402
BibRef

Wang, P.[Peng], Wang, J.D.[Jing-Dong], Zeng, G.[Gang], Feng, J.[Jie], Zha, H.B.[Hong-Bin], Li, S.P.[Shi-Peng],
Salient object detection for searched web images via global saliency,
CVPR12(3194-3201).
IEEE DOI 1208
BibRef

Xie, T.Y.[Tian-Yi], Han, W.[Wen], Xu, S.[Sheng],
YOLO-RS: A More Accurate and Faster Object Detection Method for Remote Sensing Images,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Zhao, X.F.[Xiao-Feng], Xia, Y.T.[Yu-Ting], Zhang, W.W.[Wen-Wen], Zheng, C.[Chao], Zhang, Z.L.[Zhi-Li],
YOLO-ViT-Based Method for Unmanned Aerial Vehicle Infrared Vehicle Target Detection,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Cao, F.[Feng], Xing, B.[Bing], Luo, J.C.[Jian-Cheng], Li, D.Y.[De-Yu], Qian, Y.H.[Yu-Hua], Zhang, C.[Chao], Bai, H.X.[He-Xiang], Zhang, H.[Hu],
An Efficient Object Detection Algorithm Based on Improved YOLOv5 for High-Spatial-Resolution Remote Sensing Images,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Ding, Q.Q.[Qi-Qi], Li, P.[Peng], Yan, X.F.[Xue-Feng], Shi, D.[Ding], Liang, L.[Luming], Wang, W.M.[Wei-Ming], Xie, H.R.[Hao-Ran], Li, J.[Jonathan], Wei, M.Q.[Ming-Qiang],
CF-YOLO: Cross Fusion YOLO for Object Detection in Adverse Weather with a High-Quality Real Snow Dataset,
ITS(24), No. 10, October 2023, pp. 10749-10759.
IEEE DOI 2310
BibRef

Wang, Y.M.[Yu-Ming], Zou, H.[Hua], Yin, M.[Ming], Zhang, X.[Xining],
SMFF-YOLO: A Scale-Adaptive YOLO Algorithm with Multi-Level Feature Fusion for Object Detection in UAV Scenes,
RS(15), No. 18, 2023, pp. 4580.
DOI Link 2310
BibRef

Cao, J.S.[Jin-Shan], Bao, W.S.[Wen-Shu], Shang, H.X.[Hai-Xing], Yuan, M.[Ming], Cheng, Q.[Qian],
GCL-YOLO: A GhostConv-Based Lightweight YOLO Network for UAV Small Object Detection,
RS(15), No. 20, 2023, pp. 4932.
DOI Link 2310
BibRef

Zhang, J.R.[Jia-Rui], Chen, Z.H.[Zhi-Hua], Yan, G.X.[Guo-Xu], Wang, Y.[Yi], Hu, B.[Bo],
Faster and Lightweight: An Improved YOLOv5 Object Detector for Remote Sensing Images,
RS(15), No. 20, 2023, pp. 4974.
DOI Link 2310
BibRef

Xu, W.[Wei], Ma, W.[Wenchen], Wang, S.W.[Shi-Wei], Gu, X.D.[Xu-Dong], Ni, B.B.[Bin-Bin], Cheng, W.[Wen], Feng, J.Y.[Jing-Yuan], Wang, Q.S.[Qing-Shan], Hu, M.Y.[Meng-Yao],
Automatic Detection of VLF Tweek Signals Based on the YOLO Model,
RS(15), No. 20, 2023, pp. 5019.
DOI Link 2310
BibRef

Shi, H.W.[Hou-Wang], Yang, W.Z.[Wen-Zhong], Chen, D.[Danni], Wang, M.[Min],
CPA-YOLOv7: Contextual and pyramid attention-based improvement of YOLOv7 for drones scene target detection,
JVCIR(97), 2023, pp. 103965.
Elsevier DOI 2312
Deep learning, Small target detection, Multi-scale feature fusion, Attention mechanism, Loss function BibRef

Cao, S.[Shihai], Wang, T.[Ting], Li, T.[Tao], Mao, Z.[Zehui],
UAV small target detection algorithm based on an improved YOLOv5s model,
JVCIR(97), 2023, pp. 103936.
Elsevier DOI 2312
UAV, Small target detection, Deep learning, Attention mechanism, YOLOv5 BibRef

Ahmed, M.[Mahmoud], El-Sheimy, N.[Naser], Leung, H.[Henry], Moussa, A.[Adel],
Enhancing Object Detection in Remote Sensing: A Hybrid YOLOv7 and Transformer Approach with Automatic Model Selection,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Hu, D.[Deao], Yu, M.[Mei], Wu, X.Y.[Xian-Yong], Hu, J.B.[Jing-Bo], Sheng, Y.Y.[Yu-Yang], Jiang, Y.J.[Yag-Jing], Huang, C.[Chongjing], Zheng, Y.[Yuelin],
DGW-YOLOv8: A small insulator target detection algorithm based on deformable attention backbone and WIoU loss function,
IET-IPR(18), No. 4, 2024, pp. 1096-1108.
DOI Link 2403
computer vision, image recognition, insulators, object detection BibRef

Lang, K.Q.[Kai-Qi], Cui, J.[Jie], Yang, M.Y.[Ming-Yu], Wang, H.Y.[Han-Yu], Wang, Z.L.[Zi-Long], Shen, H.H.[Hong-Hai],
A Convolution with Transformer Attention Module Integrating Local and Global Features for Object Detection in Remote Sensing Based on YOLOv8n,
RS(16), No. 5, 2024, pp. 906.
DOI Link 2403
BibRef

Wang, S.B.[Shao-Bo], Chen, R.[Renhai], Wu, H.Y.[Hong-Yue], Li, X.Z.[Xiao-Zhe], Feng, Z.Y.[Zhi-Yong],
YOLOH: You Only Look One Hourglass for Real-Time Object Detection,
IP(33), 2024, pp. 2104-2115.
IEEE DOI 2403
Feature extraction, Convolution, Object detection, MISO communication, Semantics, Computational modeling, Training, single-shot network BibRef

Shin, Y.[Yeonha], Shin, H.[Heesub], Ok, J.[Jaewoo], Back, M.Y.[Min-Young], Youn, J.[Jaehyuk], Kim, S.[Sungho],
DCEF2-YOLO: Aerial Detection YOLO with Deformable Convolution-Efficient Feature Fusion for Small Target Detection,
RS(16), No. 6, 2024, pp. 1071.
DOI Link 2403
BibRef

Zhou, J.[Jie], Yang, D.[Degang], Song, T.T.[Ting-Ting], Ye, Y.C.[Yi-Chen], Zhang, X.[Xin], Song, Y.Z.[Ying-Ze],
Improved YOLOv7 models based on modulated deformable convolution and swin transformer for object detection in fisheye images,
IVC(144), 2024, pp. 104966.
Elsevier DOI Code:
WWW Link. 2404
Fisheye image, YOLOv7, Modulated deformable convolution, Swin transformer, Object detection BibRef

Gao, X.H.[Xing-Hua], Yu, A.[Anning], Tan, J.[Jia], Gao, X.Z.[Xing-Zhong], Zeng, X.P.[Xiao-Ping], Wu, C.[Chen],
GSD-YOLOX: Lightweight and more accurate object detection models,
JVCIR(98), 2024, pp. 104009.
Elsevier DOI 2402
Vehicle detection, Lightweight, Detection accuracy, Detection speed, CCVTDB dataset BibRef

Shaikh, S.A.[Shakil A.], Chopade, J.J.[Jayant J.], Sardey, M.P.[Mohini Pramod],
Real-Time Multi-Object Detection Using Enhanced Yolov5-7S on Multi-GPU for High-Resolution Video,
IJIG(24), No. 2, March 2024, pp. 2450019.
DOI Link 2404
BibRef

Liu, K.[Kun], Qi, Y.[Yueshuang], Xu, G.F.[Guo-Feng], Li, J.L.[Jiang-Long],
YOLOv5s maritime distress target detection method based on swin transformer,
IET-IPR(18), No. 5, 2024, pp. 1258-1267.
DOI Link 2404
image processing, object detection, object recognition BibRef

Xiao, Y.[Yun], Liao, H.[Hai],
LIDA-YOLO: An unsupervised low-illumination object detection based on domain adaptation,
IET-IPR(18), No. 5, 2024, pp. 1178-1188.
DOI Link 2404
image enhancement, object detection, unsupervised learning BibRef

Shao, Y.H.[Yan-Hua], Huang, Q.[Qimeng], Mei, y.[yanying], Chu, h.[hongyu],
MOD-YOLO: Multispectral object detection based on transformer dual-stream YOLO,
PRL(183), 2024, pp. 26-34.
Elsevier DOI 2406
Feature fusion, Multispectral object detection, Transformer, Lightweight model BibRef

Jooshin, H.K.[Hadi Khodaei], Nangir, M.[Mahdi], Seyedarabi, H.[Hadi],
Inception-YOLO: Computational cost and accuracy improvement of the YOLOv5 model based on employing modified CSP, SPPF, and inception modules,
IET-IPR(18), No. 8, 2024, pp. 1985-1999.
DOI Link 2406
convolutional neural nets, image processing, object detection BibRef

Chaurasia, D.[Divyansh], Patro, B.D.K.,
Detection of objects in satellite and aerial imagery using channel and spatially attentive YOLO-CSL for surveillance,
IVC(147), 2024, pp. 105070.
Elsevier DOI 2406
Remote sensing, Computer vision, Channel attention, Spatial attention, Rotational object detection, Circular smooth label BibRef


Gupta, K.[Kartik], Asthana, A.[Akshay],
Reducing the Side-Effects of Oscillations in Training of Quantized YOLO Networks,
WACV24(2440-2449)
IEEE DOI 2404
YOLO, Training, Quantization (signal), Image edge detection, Semantic segmentation, Memory management, Algorithms, Image recognition and understanding BibRef

Chen, L.F.[Lun-Feng], Luo, C.Z.[Cheng-Zhi], Li, X.[Xiao], Xiao, J.X.[Ji-Xiang],
Rotating target detection algorithm in remote sensing images based on improved YOLOv5s,
CVIDL23(180-184)
IEEE DOI 2403
Training, Deep learning, Computational modeling, Semantics, Object detection, Predictive models, Feature extraction, component, attention mechanism BibRef

Feng, S.X.[Shu-Xuan], Lu, J.[Jun],
Research on image recognition based on neural network model learning algorithm,
CVIDL23(21-24)
IEEE DOI 2403
Training, Deep learning, Image recognition, Head, Computational modeling, Neural networks, Object Detection, YOLOv5s, Attention Mechanism BibRef

Dou, X.K.[Xin-Ke], Wang, T.[Ting], Shao, S.L.[Shi-Liang],
A Lightweight YOLOv5 Model Integrating GhostNet and Attention Mechanism,
CVIDL23(348-352)
IEEE DOI 2403
Training, Deep learning, Computational modeling, Neural networks, Object detection, Detectors, Feature extraction, YOLOv5, Ghost, NAM, CBAM BibRef

Kumar, P.[Piyush], Kumar, V.[Vimal],
Exploring the Frontier of Object Detection: A Deep Dive into YOLOv8 and the COCO Dataset,
ICCVMI23(1-6)
IEEE DOI 2403
YOLO, Measurement, Analytical models, Reviews, Annotations, Computer architecture, YOLO8 BibRef

Lazarevich, I.[Ivan], Grimaldi, M.[Matteo], Kumar, R.[Ravish], Mitra, S.[Saptarshi], Khan, S.[Shahrukh], Sah, S.[Sudhakar],
YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systems,
REDLCV23(1161-1170)
IEEE DOI Code:
WWW Link. 2401
BibRef

Campos, F.[Filipe], Cerqueira, F.G.[Francisco Gonçalves], Cruz, R.P.M.[Ricardo P. M.], Cardoso, J.S.[Jaime S.],
YOLOMM: You Only Look Once for Multi-modal Multi-tasking,
CIARP23(I:564-574).
Springer DOI 2312
BibRef

Wang, C.Y.[Chien-Yao], Bochkovskiy, A.[Alexey], Liao, H.Y.M.[Hong-Yuan Mark],
YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors,
CVPR23(7464-7475)
IEEE DOI 2309
BibRef

Li, G.[Guofa], Zhang, Y.J.[Ying-Jie], Ouyang, D.[Delin], Qu, X.D.[Xing-Da],
An Improved Lightweight Network Based on Yolov5s for Object Detection in Autonomous Driving,
AVVision22(585-601).
Springer DOI 2304
BibRef

Nanlin, W.[Wei], Wei, H.[Huang],
Research on Unmanned Vehicle Detection Method Based on Improved YOLOv4_Tiny,
ICRVC22(129-135)
IEEE DOI 2301
Training, Image segmentation, Computational modeling, Data models, Automobiles, Autonomous vehicles, YOLOv4_Tiny, data augmentation, feature scale BibRef

Wang, Y.Z.[Yun-Zhen], Ma, H.B.[Hong-Bing], Li, L.L.[Liang-Liang],
Road Traffic Vehicle Detection Method Using Lightweight YOLOv5 and Attention Mechanism,
ICIVC22(201-207)
IEEE DOI 2301
Convolution, Computational modeling, Roads, Object detection, Data models, Intelligent transportation systems, Testing, depthwise separable convolution BibRef

Cao, K.Y.[Kai-Yang], Cui, X.[Xu], Piao, J.C.[Jin-Chun],
Smaller Target Detection Algorithms Based on YOLOv5 in Safety Helmet Wearing Detection,
ICRVC22(154-158)
IEEE DOI 2301
Head, Computational modeling, Robot kinematics, Object detection, Safety, Task analysis, Deep learning, Activation function BibRef

Han, R.[Rong], Liu, X.H.[Xiao-Hong], Chen, T.[Ting],
Yolo-SG: Salience-Guided Detection Of Small Objects In Medical Images,
ICIP22(4218-4222)
IEEE DOI 2211
Deep learning, Analytical models, Image resolution, Object detection, Medical services, Lesions, Data mining, object detection BibRef

Wang, C.Z.[Chun-Zhi], Tong, X.[Xin], Zhu, J.H.[Jia-Hui], Gao, R.[Rong],
Ghost-YOLOX: A Lightweight and Efficient Implementation of Object Detection Model,
ICPR22(4552-4558)
IEEE DOI 2212
Training, Image segmentation, Costs, Convolution, Fuses, Computational modeling, Object detection, Object detection, Multi-scale pyramidal convolution BibRef

Ganesh, P.[Prakhar], Chen, Y.[Yao], Yang, Y.[Yin], Chen, D.[Deming], Winslett, M.[Marianne],
YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs,
WACV22(1311-1321)
IEEE DOI 2202
Performance evaluation, Deep learning, Image edge detection, Transfer learning, Neural networks, Object Detection/Recognition/Categorization Vision Systems and Applications BibRef

Javed, M.G.[Muhammad Gohar], Raza, M.[Minahil], Ghaffar, M.M.[Muhammad Mohsin], Weis, C.[Christian], Wehn, N.[Norbert], Shahzad, M.[Muhammad], Shafait, F.[Faisal],
QuantYOLO: A High-Throughput and Power-Efficient Object Detection Network for Resource and Power Constrained UAVs,
DICTA21(01-08)
IEEE DOI 2201
Quantization (signal), Power demand, Network topology, Object detection, Throughput, Topology, Real-Time and Power-Efficient Architecture BibRef

Li, J.Q.[Jia-Qi], Zhao, Y.[Yanan], Gao, L.[Li], Cui, F.[Feng],
Compression of YOLOv3 via Block-Wise and Channel-Wise Pruning for Real-Time and Complicated Autonomous Driving Environment Sensing Applications,
ICPR21(5107-5114)
IEEE DOI 2105
Training, Solid modeling, Visualization, Pipelines, Object detection, Real-time systems, Sensors BibRef

Wang, Y.[Ya], Zell, A.[Andreas],
Yolo+FPN: 2D and 3D Fused Object Detection With an RGB-D Camera,
ICPR21(4657-4664)
IEEE DOI 2105
Training, Visualization, Fuses, Object detection, Benchmark testing, Cameras BibRef

Li, L.W.[Long-Wei], Xi, J.B.[Jiang-Bo], Jiang, W.D.[Wan-Dong], Cong, M.[Ming], Han, L.[Ling], Yang, Y.[Yun],
Multi-scale Fast Detection of Objects in High Resolution Remote Sensing Images,
ICIVC20(5-10)
IEEE DOI 2009
Remote sensing, Feature extraction, Image resolution, Object detection, Machine learning, Data models, YOLOv3 BibRef

Koksal, A., Ince, K.G., Alatan, A.A.[A. Aydin],
Effect of Annotation Errors on Drone Detection with YOLOv3,
Anti-UAV20(4439-4447)
IEEE DOI 2008
Detectors, Training, Feature extraction, Labeling, Real-time systems, Measurement, Drones BibRef

Choi, J., Chun, D., Kim, H., Lee, H.,
Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving,
ICCV19(502-511)
IEEE DOI 2004
object detection, road safety, traffic engineering computing, object detection algorithms, Gaussian YOLOv3, Feature extraction BibRef

Simon, M.[Martin], Milz, S.[Stefan], Amende, K.[Karl], Gross, H.M.[Horst-Michael],
Complex-YOLO: An Euler-Region-Proposal for Real-Time 3D Object Detection on Point Clouds,
CVRoads18(I:197-209).
Springer DOI 1905
Lidar, automated driving. BibRef

Redmon, J.[Joseph], Farhadi, A.[Ali],
YOLO9000: Better, Faster, Stronger,
CVPR17(6517-6525)
IEEE DOI 1711
Award, CVPR, HM. Detectors, Feature extraction, Image resolution, Object detection, Real-time systems, Training Real time, 9000 object categories. BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
SWIN Transformer .


Last update:Jul 18, 2024 at 20:50:34