SINet: A Scale-Insensitive Convolutional Neural Network for Fast Vehicle Detection

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148

Deep learning

LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 73,472

You Only Look Once: Unified, Real-Time Object Detection

Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.91 · Cited by 53,803

ImageNet Large Scale Visual Recognition Challenge

Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380

Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.81 · Cited by 32,684

Untitled work

(2016) · Cited by 31,590

Feature Pyramid Networks for Object Detection

Lin, T.-Y., Dollar, P., Girshick, R., He, K., Hariharan, B., & Belongie, S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.106 · Cited by 30,939

Fast R-CNN

Girshick, R. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.169 · Cited by 28,105

Part-Aware Region Proposal for Vehicle Detection in High Occlusion Environment

Zhang, W., Zheng, Y., Gao, Q., & Mi, Z. (2019) · IEEE Access · doi:10.1109/access.2019.2929432 · Cited by 27

A Lightweight CNN Model for Refining Moving Vehicle Detection From Satellite Videos

Chen, R., Li, X., & Li, S. (2020) · IEEE Access · doi:10.1109/access.2020.3040977 · Cited by 28

LiCaNet: Further Enhancement of Joint Perception and Motion Prediction Based on Multi-Modal Fusion

Khalil, Y. H., & Mouftah, H. T. (2022) · IEEE Open Journal of Intelligent Transportation Systems · doi:10.1109/ojits.2022.3160888 · Cited by 27

A modified deep learning architecture for vehicle detection in traffic monitoring system

Haritha, H., & Thangavel, S. K. (2019) · International Journal of Computers and Applications · doi:10.1080/1206212x.2019.1662171 · Cited by 29

Vehicle Detection and Disparity Estimation Using Blended Stereo Images

Zhou, C., Liu, Y., Sun, Q., & Lasang, P. (2021) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2020.3049008 · Cited by 26

Safety and Risk Analysis of Autonomous Vehicles Using Computer Vision and Neural Networks

Dixit, A., Chidambaram, R. K., & Allam, Z. (2021) · Vehicles · doi:10.3390/vehicles3030036 · Cited by 26

Pedestrian- and Vehicle-Detection Algorithm Based on Improved Aggregated Channel Features

Hua, J., Shi, Y., Xie, C., Zhang, H., & Zhang, J. (2021) · IEEE Access · doi:10.1109/access.2021.3057616 · Cited by 24

Double FCOS: A Two-Stage Model Utilizing FCOS for Vehicle Detection in Various Remote Sensing Scenes

Gao, P., Tian, T., Zhao, T., Li, L., Zhang, N., & Tian, J. (2022) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2022.3181594 · Cited by 24

A lightweight deep neural network with higher accuracy

Zhao, L., Wang, L., Jia, Y., & Cui, Y. (2022) · PLoS ONE · doi:10.1371/journal.pone.0271225 · Cited by 24

A Dynamic Transformer Network for Vehicle Detection

Tian, C., Liu, K., Zhang, B., Huang, Z., Lin, C., & Zhang, D. D. (2025) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2025.3565318 · Cited by 24

Oil Well Detection via Large-Scale and High-Resolution Remote Sensing Images Based on Improved YOLO v4

Shi, P., Jiang, Q., Shi, C., Xi, J., Tao, G., Zhang, S., Zhang, Z., Liu, B., Gao, X., & Wu, Q. (2021) · Remote Sensing · doi:10.3390/rs13163243 · Cited by 25

Dense Traffic Detection at Highway-Railroad Grade Crossings

Guo, F., Jiang, Z., Wang, Y., Chen, C., & Qian, Y. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3140948 · Cited by 22

Detection Technique Tailored for Small Targets on Water Surfaces in Unmanned Vessel Scenarios

Zhang, J., Huang, W., Zhuang, J., Zhang, R., & Du, X. (2024) · Journal of Marine Science and Engineering · doi:10.3390/jmse12030379 · Cited by 23

Real-Time Monocular Joint Perception Network for Autonomous Driving

Li, K., Xiong, H., Liu, J., Xu, Q. Y., & Wang, J. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3146087 · Cited by 21

Representative Feature Alignment for Adaptive Object Detection

Xu, S., Zhang, H., Xu, X., Hu, X., Xu, Y., Dai, L., Choi, K., & Heng, P. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2022.3202094 · Cited by 21

A fast and effective video vehicle detection method leveraging feature fusion and proposal temporal link

Yang, Y., Song, H., Sun, S., Zhang, W., Chen, Y., Rakai, L., & Fang, Y. (2021) · Journal of Real-Time Image Processing · doi:10.1007/s11554-021-01121-y · Cited by 22

Built-in Depth-Semantic Coupled Encoding for Scene Parsing, Vehicle Detection, and Road Segmentation

Liu, S., Zhang, H., Shao, L., & Yang, J. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.2987819 · Cited by 20

Vehicle Detection in Very-High-Resolution Remote Sensing Images Based on an Anchor-Free Detection Model with a More Precise Foveal Area

Li, X., Men, F., Lv, S., Jiang, X., Pan, M., Ma, Q., & Yu, H. (2021) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi10080549 · Cited by 21

An Automated Learning Framework With Limited and Cross-Domain Data for Traffic Equipment Detection From Surveillance Videos

Zhou, W., Liu, Y., Wang, C., Zhan, Y.-F., Dai, Y., & Wang, R. (2022) · IEEE transactions on intelligent transportation systems (Print) · doi:10.1109/tits.2022.3195509 · Cited by 19

Knowledge Fusion Distillation: Improving Distillation with Multi-scale Attention Mechanisms

Li, L., Su, W., Liu, F., He, M., & Liang, X. (2023) · Neural Processing Letters · doi:10.1007/s11063-022-11132-w · Cited by 23

Real-time dense traffic detection using lightweight backbone and improved path aggregation feature pyramid network

Guo, F., Wang, Y., & Qian, Y. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2022.100427 · Cited by 19

Identification of distinguishing characteristics of intersections based on statistical analysis and data from video cameras

Shepelev, V., Aliukov, S. V., Glushkov, A., & Галиевич, Ш. С. (2020) · Journal Of Big Data · doi:10.1186/s40537-020-00324-7 · Cited by 18

CODAN: Counting-driven Attention Network for Vehicle Detection in Congested Scenes

Li, W., Wang, Z., Wu, X. Y., Zhang, J., Peng, Q., & Li, H. (2020) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3394171.3413945 · Cited by 19

The data conundrum: compression of automotive imaging data and deep neural network based perception

Chan, P. H., Souvalioti, G., Huggett, A., Kirsch, G., & Donzella, V. (2021) · London Imaging Meeting · doi:10.2352/issn.2694-118x.2021.lim-78 · Cited by 18

Traffic incident detection based on a global trajectory spatiotemporal map

Liang, H., Song, H., Yun, X., Sun, S., Wang, Y., & Zhang, Z. (2021) · Complex & Intelligent Systems · doi:10.1007/s40747-021-00602-8 · Cited by 18

A Traffic Event Detection Method Based on Random Forest and Permutation Importance

Su, Z., Liu, Q., Zhao, C., & Sun, F. (2022) · Mathematics · doi:10.3390/math10060873 · Cited by 18

A Review on Object Detection Based on Deep Convolutional Neural Networks for Autonomous Driving

Lu, J., Tang, S., Wang, J., Zhu, H., & Wang, Y. (2019) · 2019 Chinese Control And Decision Conference (CCDC) · doi:10.1109/ccdc.2019.8832398 · Cited by 17

Unc-SOD: An Uncertainty Learning Framework for Small Object Detection

Yuan, X., Cheng, G., Cheng, J., Yao, R., & Han, J. (2026) · IEEE Transactions on Image Processing · doi:10.1109/tip.2026.3654892 · Cited by 18

A Two-Stage Hybrid Extreme Learning Model for Short-Term Traffic Flow Forecasting

Cui, Z., Huang, B., Dou, H., Cheng, Y., Guan, J., & Zhou, T. (2022) · Mathematics · doi:10.3390/math10122087 · Cited by 17

Cutting‐Edge Deep Learning Methods for Image‐Based Object Detection in Autonomous Driving: In‐Depth Survey

Saeedizadeh, N., Jalali, S. M. J., Khan, B., & Mohamed, S. M. K. (2025) · Expert Systems · doi:10.1111/exsy.70020 · Cited by 18

Multiscale Gaussian Attention Mechanism for Tiny-Object Detection in Remote Sensing Images

Shi, S., Fang, Q., Xu, X., & Dong, D. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3591260 · Cited by 19

Orientation aware weapons detection in visual data: a benchmark dataset

Haq, N. U., Fraz, M. M., Hashmi, T. S. S., & Shahzad, M. S. (2022) · Computing · doi:10.1007/s00607-022-01095-0 · Cited by 16

DALocNet: Improving Localization Accuracy for Domain Adaptive Object Detection

Yu, Y., Xu, X., Hu, X., & Heng, P. (2019) · IEEE Access · doi:10.1109/access.2019.2915607 · Cited by 16

Eliminating cross-camera bias for vehicle re-identification

Peng, J., Jiang, G., Chen, D., Zhao, T., Wang, H., & Fu, X. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09987-z · Cited by 15

Mixed Stage Partial Network and Background Data Augmentation for Surveillance Object Detection

Chen, P.-Y., Hsieh, J.-W., Gochoo, M., & Chen, Y. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3206709 · Cited by 14

Dynamic Feature Focusing Network for small object detection

Jing, R., Zhang, W., Li, Y., Li, W., & Liu, Y. (2024) · Information Processing & Management · doi:10.1016/j.ipm.2024.103858 · Cited by 15

Making You Only Look Once Faster: Toward Real-Time Intelligent Transportation Detection

Dai, Y., Liu, W., Xie, W., Liu, R., Zheng, Z., Long, K., Wang, L., Mao, L., Qiu, Q., & Ling, G. (2022) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2022.3201400 · Cited by 15

PerspectiveNet: An Object Detection Method With Adaptive Perspective Box Network Based on Density-Aware

Li, C., Qu, Z., & Wang, S.-Y. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3240616 · Cited by 14

Optimizing Road Traffic Surveillance: A Robust Hyper-Heuristic Approach for Vehicle Segmentation

Rodrí­guez-Esparza, E., Ramos-Soto, O., Masegosa, A. D., Onieva, E., Oliva, D. A., Arriandiaga, A., & Ghosh, A. (2024) · IEEE Access · doi:10.1109/access.2024.3369039 · Cited by 13

Defect Detection Scheme for Key Equipment of Transmission Line for Complex Environment

Wang, J., Deng, F., & Wei, B. (2022) · Electronics · doi:10.3390/electronics11152332 · Cited by 13

An Efficient and Scene-Adaptive Algorithm for Vehicle Detection in Aerial Images Using an Improved YOLOv3 Framework

Zhang, X., & Zhu, X. (2019) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi8110483 · Cited by 13

How Would Image Down-Sampling and Compression Impact Object Detection in the Context of Self-driving Vehicles ?

Bouderbal, I., Amamra, A., & Benatia, M. A. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-69418-0_3 · Cited by 13

AlexDarkNet: Hybrid CNN architecture for real-time Traffic monitoring with unprecedented reliability

Bhardwaj, R. J., & Rao, D. S. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-09450-2 · Cited by 12

Vehicle detection in varied weather conditions using enhanced deep YOLO with complex wavelet

Kiran, V. K., Dash, S., & Parida, P. (2024) · Engineering Research Express · doi:10.1088/2631-8695/ad507d · Cited by 14

Assessment of Landsat Based Deep-Learning Membership Analysis for Development of from–to Change Time Series in the Prairie Region of Canada from 1984 to 2018

Pouliot, D., Alavi, N., Wilson, S., Duffe, J., Pasher, J., Davidson, A., Daneshfar, B., & Lindsay, E. (2021) · Remote Sensing · doi:10.3390/rs13040634 · Cited by 15

Deeply Supervised Z-Style Residual Network Devotes to Real-Time Environment Perception for Autonomous Driving

Dai, X., Yuan, X., Liu, P., & Wei, X. (2019) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2019.2918227 · Cited by 12

Kl-Divergence-Based Region Proposal Network For Object Detection

Seo, G., Yoo, J., Cho, J., & Kwak, N. (2020) · Proceedings - International Conference on Image Processing · doi:10.1109/icip40778.2020.9191075 · Cited by 12

Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes

Yang, C., Ablavsky, V., Wang, K., Feng, Q., & Betke, M. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58523-5_31 · Cited by 12

A real-time multi-vehicle tracking framework in intelligent vehicular networks

Fu, H., Guan, J., Feng, J., Wang, C., & Ma, H. (2021) · China Communications · doi:10.23919/jcc.2021.06.008 · Cited by 12

A Step-Wise Domain Adaptation Detection Transformer for Object Detection under Poor Visibility Conditions

Zhang, G., Wang, L., & Chen, Z. (2024) · Remote Sensing · doi:10.3390/rs16152722 · Cited by 13

R-Net: Recursive decoder with edge refinement network for salient object detection

Wang, H., Zhao, Y., Zhang, F., Gui, G., Yu, L., Chen, B., Liao, M., Yang, C., & Gui, W. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125562 · Cited by 11

CFENet: Contextual Feature Enhancement Network for Tiny Object Detection in Aerial Images

Hu, H., Chen, S.-B., & Tang, J. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3556469 · Cited by 13

Real-Time Vehicle Detection in Satellite Videos: Transitioning From Large Scenes to Clusters

Pan, J., Gu, Y., Gao, G., & Wu, S. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3581150 · Cited by 15

Learning a Layout Transfer Network for Context Aware Object Detection

Wang, T., He, X., Cai, Y., & Xiao, G. (2019) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2019.2939213 · Cited by 11

Small vehicle classification in the wild using generative adversarial network

Wang, X., Chen, X., & Wang, Y. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-05331-6 · Cited by 11

Learning to See in Nighttime Driving Scenes with Inter-frequency Priors

Fan, Z., Wu, X., Chen, X., & Li, Y. (2023) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw59228.2023.00444 · Cited by 10

Super-Resolution GAN and Global Aware Object Detection System for Vehicle Detection in Complex Traffic Environments

Wang, H., Chaw, J. K., Goh, S. K., Shi, L., Tin, T. T., Huang, N., & Gan, H. (2024) · IEEE Access · doi:10.1109/access.2024.3442484 · Cited by 12

The Role of AI in Smart Mobility: A Comprehensive Survey

Coco, M. D., Carcagnì, P., Trilles, S., Iskandaryan, D., & Leo, M. (2025) · Electronics · doi:10.3390/electronics14091801 · Cited by 12

Multiscale Feature Learning Based on Enhanced Feature Pyramid for Vehicle Detection

Nguyen, H. (2021) · Complexity · doi:10.1155/2021/5555121 · Cited by 10

Real-Time Vehicle Detection for Surveillance of River Dredging Areas Using Convolutional Neural Networks

Bayati, M. A. Z. A., & Çakmak, M. (2023) · International Journal of Image Graphics and Signal Processing · doi:10.5815/ijigsp.2023.05.02 · Cited by 10

Vehicle Detection in UAV Aerial Images Based on Improved YOLOv3

Zhang, S., Chai, L., & Jin, L. (2020) · IEEE International Conference on Networking, Sensing and Control (ICNSC) · doi:10.1109/icnsc48988.2020.9238059 · Cited by 10

Vehicle Detection in Remote Sensing Image Based on Machine Vision

Zhou, L., Chang, Z., Yan, H., Zuo, X., Qiao, B., Zhou, B., Fan, M., & Liu, Y. (2021) · Computational Intelligence and Neuroscience · doi:10.1155/2021/8683226 · Cited by 10

A complementary and precise vehicle detection approach in RGB-T images via semi-supervised transfer learning and decision-level fusion

Zhang, X. X., Lu, X. Y., & Peng, L. (2022) · International Journal of Remote Sensing · doi:10.1080/01431161.2021.2008543 · Cited by 10

Recent Advances in Vision-Based On-Road Behaviors Understanding: A Critical Survey

Trabelsi, R., Khemmar, R., Decoux, B., Ertaud, J.-Y., & Boutteau, R. (2022) · Sensors · doi:10.3390/s22072654 · Cited by 10

Orientation Aware Object Detection with Application to FirearmsPreprint

Iqbal, J., Munir, M. A., Mahmood, A., Ali, A. R., & Ali, M. (2019) · arXiv (Cornell University) · doi:10.13140/rg.2.2.34648.75522 · Cited by 10

Partner learning: A comprehensive knowledge transfer for vehicle re-identification

Qian, W., He, Z., Chen, C., & Peng, S. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.01.043 · Cited by 9

Advancing vehicle detection for autonomous driving: integrating computer vision and machine learning techniques for real-world deployment

Farag, W., & Fayed, M. (2025) · Journal of Control and Decision · doi:10.1080/23307706.2025.2469893 · Cited by 12

Vision technologies in autonomous vehicles: progress, methodologies, and key challenges

Kumar, H., Mamoria, P., & Dewangan, D. K. (2025) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-025-02912-3 · Cited by 12

All you need for object detection: From pixels, points, and prompts to Next-Gen fusion and multimodal LLMs/VLMs in autonomous vehicles

Boroujeni, S. P. H., Mehrabi, N., Alzorgan, H., Fazeli, M., & Razi, A. (2026) · Image and Vision Computing · doi:10.1016/j.imavis.2026.105944 · Cited by 9

A Multibranch Object Detection Method for Traffic Scenes

Feng, J., Wang, F., Feng, S., & Peng, Y. (2019) · Computational Intelligence and Neuroscience · doi:10.1155/2019/3679203 · Cited by 9

Research on Object Detection Algorithm Based on Multilayer Information Fusion

Chen, B.-Y., Shen, Y.-K., & Sun, K. (2020) · Mathematical Problems in Engineering · doi:10.1155/2020/9076857 · Cited by 9

Vehicle Detection with Self-Training for Adaptative Video Processing Embedded Platform

Cygert, S., & Czyżewski, A. (2020) · Applied Sciences · doi:10.3390/app10175763 · Cited by 11

A new comparison framework to survey neural networks‐based vehicle detection and classification approaches

Hashemi, S., Emami, H., & Sangar, A. B. (2021) · International Journal of Communication Systems · doi:10.1002/dac.4928 · Cited by 9

GSDerainNet: A Deep Network Architecture Based on a Gaussian Shannon Filter for Single Image Deraining

Yao, Y., Shi, Z., Hu, H., Li, J., Wang, G., & Liu, L. (2023) · Remote Sensing · doi:10.3390/rs15194825 · Cited by 8

Traffic Noise Assessment Using Intelligent Acoustic Sensors (Traffic Ear) and Vehicle Telematics Data

Ghaffarpasand, O., Almojarkesh, A., Morris, S., Stephens, E., Chalabi, A., Almojarkesh, U., Almojarkesh, Z., & Pope, F. D. (2023) · Sensors · doi:10.3390/s23156964 · Cited by 8

Optimizing Object Detection Efficiency for Autonomous Vehicles through the Integration of YOLOv4 and EfficientDet Algorithms

Rajan, V. A., Sakhamuri, S., Nayaki, A. P., Agarwal, S., Aeron, A., & Shri, M. L. (2024) · International Conference on Trends in Quantum Computing and Emerging Business Technologies (TQCEBT) · doi:10.1109/tqcebt59414.2024.10545157 · Cited by 8

Small object detection combining attention mechanism and a novel FPN

Chen, J., Liu, S., Zhao, L., Chen, D., & Wei-hua, Z. (2021) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-211905 · Cited by 9

Multi-Pedestrian Tracking Based on KC-YOLO Detection and Identity Validity Discrimination Module

Li, J., Wu, W., Zhang, D., Fan, D., Jiang, J., Lu, Y., Gao, E., & Yue, T. (2023) · Applied Sciences · doi:10.3390/app132212228 · Cited by 8

A lightweight vehicle detection network fusing feature pyramid and channel attention

Lu, J. G., Huang, T., Zhang, Q., Chen, X., & Zhou, J. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101166 · Cited by 8

Power Quality Improvement of Integrated PV System with PID Controller Based Shunt Active Filter

Reddy, D. R., Aravindh, V., Kondalu, M., Reddy, C. R., Sekhar, O. C., & Pandian, A. (2022) · IEEE North Karnataka Subsection Flagship International Conference (NKCon) · doi:10.1109/nkcon56289.2022.10126567 · Cited by 7

A Multi-scale Feature Fusion Network Focusing on Small Objects in UAV-View

Li, J., Yu, C., Wei, W., Li, J., Huang, K., Hussian, A., Liu, X., & Zhou, Y. (2025) · Cognitive Computation · doi:10.1007/s12559-025-10445-x · Cited by 12

Application of Convolution Neural Network (CNN) Model Combined with Pyramid Algorithm in Aerobics Action Recognition

Liang, Q. (2021) · Computational Intelligence and Neuroscience · doi:10.1155/2021/6170070 · Cited by 7

Efficient multi-model integration neural network framework for nighttime vehicle detection

Li, J., Xiao, D., & Yang, Q. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12857-5 · Cited by 7

Vehicle detection in diverse traffic using an ensemble convolutional neural backbone via feature concatenation

Deshmukh, P., Majhi, S., Sahoo, U. K., & Das, S. K. (2023) · Transportation Letters · doi:10.1080/19427867.2023.2250622 · Cited by 7

Transfer Learning of Pre-Trained CNN Models for Fingerprint Liveness Detection

Samma, H., & Suandi, S. A. (2020) · IntechOpen eBooks · doi:10.5772/intechopen.93473 · Cited by 7

A Study for Selecting the Best One-Stage Detector for Autonomous Driving

Chun, D., Choi, J., Kim, H., & Lee, H. (2019) · International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) · doi:10.1109/itc-cscc.2019.8793291 · Cited by 7

The One-Stage Detector Algorithm Based on Background Prediction and Group Normalization for Vehicle Detection

Lu, F., Xie, F., Shen, S., Yang, J., Zhao, J., Sun, R., & Huang, L. (2020) · Applied Sciences · doi:10.3390/app10175883 · Cited by 7

Occlusion-Aware Detection for Internet of Vehicles in Urban Traffic Sensing Systems

Chen, L., Ruan, Y., Fan, H., Zhu, H., Chen, X., & Chen, Q. (2020) · Mobile Networks and Applications · doi:10.1007/s11036-020-01668-3 · Cited by 7

Vehicle Detection in Deep LearningPreprint

Xiao, Y. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.13390 · Cited by 8

Machine Learning-Based Real-Time Traffic Control System

Jain, S., Singh, A., Shah, S. N., Lalam, R., & Saxena, D. (2021) · IEEE Mysore Sub Section International Conference (MysuruCon) · doi:10.1109/mysurucon52639.2021.9641643 · Cited by 6

Deep Learning Methods Application for Object Detection Tasks Using Unmanned Aerial Vehicles

Babaryka, A., Katerynchuk, I., Klymash, M. M., & ЧЕСАНОВСЬКИЙ, І. (2022) · IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET) · doi:10.1109/tcset55632.2022.9766891 · Cited by 6

Semi‐MoreGAN: Semi‐supervised Generative Adversarial Network for Mixture of Rain Removal

Shen, Y., Wang, Y., Wei, M., Chen, H., Xie, H., Cheng, G., & Wang, F. L. (2022) · Computer Graphics Forum · doi:10.1111/cgf.14690 · Cited by 6

Enhanced real-time road-vehicles’ detection and tracking for driving assistance

Farag, W., & Nadeem, M. (2024) · International Journal of Knowledge-based and Intelligent Engineering Systems · doi:10.3233/kes-230062 · Cited by 7

Traffic state prediction using conditionally Gaussian observed Markov fuzzy switching model

Bouyahia, Z., Haddad, H., Derrode, S., & Wojciech Pieczynski, E. (2022) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2022.2069498 · Cited by 6

Vehicle Detection using Artificial Intelligence based Algorithm in Intelligent Transportation Systems

Waqar, M., Ishaq, M., Afzal, M. H., & Iqbal, S. (2023) · International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) · doi:10.1109/icomet57998.2023.10099381 · Cited by 6

Continual Learning with Bayesian Model Based on a Fixed Pre-Trained Feature ExtractorPreprint

Yang, Y., Cui, Z., Xu, J., Zhong, C., Zheng, W., & Wang, R. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4152856 · Cited by 6

Deep Learning for Small and Tiny Object Detection: A Survey

Kos, A., Belter, D., & Majek, K. (2023) · Pomiary, Automatyka, Robotyka · doi:10.14313/par_249/85 · Cited by 7

VP-YOLO: Robust Vehicle-Pedestrian Detection in Challenging Traffic Scenarios via A Human Visual Perception-Inspired Network

Liu, W., Deng, T., & Yan, F. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889912 · Cited by 5

Vehicle detection in CCTV with global-guided self-attention and convolution

Guo, Y., Yamamoto, Y., Yaginuma, H., & Taniguchi, Y. (2025) · Complex & Intelligent Systems · doi:10.1007/s40747-025-02073-7 · Cited by 6

A Scale-Insensitive Convolutional Neural Network for Fast Vehicle Detection

Jadhav, S. D. (2019) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2019.6296 · Cited by 3

Scale optimization for full-image-CNN vehicle detection

Gao, Y., Guo, S., Huang, K., Chen, J., Gong, Q., Zou, Y., Bai, T., & Overett, G. (2017) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2017.7995812 · Cited by 33

Improving Faster R‐CNN Framework for Fast Vehicle Detection

Nguyen, H. (2019) · Mathematical Problems in Engineering · doi:10.1155/2019/3808064 · Cited by 80

Scale-Aware RPN for Vehicle Detection

Ding, L., Wang, Y., Laganière, R., Luo, X., & Fu, S. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-03801-4_43 · Cited by 6

A modified deep learning architecture for vehicle detection in traffic monitoring system

Haritha, H., & Thangavel, S. K. (2019) · International Journal of Computers and Applications · doi:10.1080/1206212x.2019.1662171 · Cited by 29