Improved YOLOv4 approach: A real time occluded vehicle detection

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 56,035 · see citing works

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 · see citing works

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 · see citing works

YOLO9000: Better, Faster, Stronger

Redmon, J., & Farhadi, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.690 · Cited by 19,892 · see citing works

YOLOv4: Optimal Speed and Accuracy of Object Detection

Bochkovskiy, A., Wang, C.-Y., & Liao, H.-Y. M. (2020) · arXiv · doi:10.48550/arxiv.2004.10934 · Cited by 10,307 · see citing works

Object Detection With Deep Learning: A Review

Zhao, Z.-Q., Zheng, P., Xu, S.-T., & Wu, X. (2019) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2876865 · Cited by 5,545 · see citing works

A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

Cai, Z., Fan, Q., Feris, R. S., & Vasconcelos, N. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46493-0_22 · Cited by 1,605 · see citing works

Feature Selective Anchor-Free Module for Single-Shot Object Detection

Zhu, C., He, Y., & Savvides, M. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00093 · Cited by 1,066 · see citing works

Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in VideoPreprint

Shafiee, M., Chywl, B., Li, F., & Wong, A. (2017) · arXiv.org · doi:10.48550/arxiv.1709.05943 · Cited by 403 · see citing works

Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video

Shaifee, M. J., Chywl, B., Li, F., & Wong, A. M. (2017) · Journal of Computational Vision and Imaging Systems · doi:10.15353/vsnl.v3i1.171 · Cited by 370 · see citing works

Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining

Tang, T., Zhou, S., Deng, Z., Zou, H., & Lei, L. (2017) · Sensors · doi:10.3390/s17020336 · Cited by 282 · see citing works

On the Performance of One-Stage and Two-Stage Object Detectors in Autonomous Vehicles Using Camera Data

Carranza-García, M., Torres-Mateo, J., Lara-Benítez, P., & García-Gutiérrez, J. (2020) · Remote Sensing · doi:10.3390/rs13010089 · Cited by 270 · see citing works

An Improved YOLOv2 for Vehicle Detection

Sang, J., Wu, Z., Guo, P., Hu, H., Xiang, H., Zhang, Q., & Cai, B. (2018) · Sensors · doi:10.3390/s18124272 · Cited by 223 · see citing works

Probabilistic two-stage detectionPreprint

Zhou, X., Koltun, V., & Krähenbühl, P. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.07461 · Cited by 219 · see citing works

Real Time Pear Fruit Detection and Counting Using YOLOv4 Models and Deep SORT

Parico, A. I. B., & Ahamed, T. (2021) · Sensors · doi:10.3390/s21144803 · Cited by 202 · see citing works

A small attentional YOLO model for landslide detection from satellite remote sensing images

Cheng, L., Li, J., Duan, P., & Wang, M. (2021) · Landslides · doi:10.1007/s10346-021-01694-6 · Cited by 179 · see citing works

$L1$ -Norm Batch Normalization for Efficient Training of Deep Neural Networks

Wu, S., Li, G., Deng, L., Liu, L., Wu, D., Xie, Y., & Shi, L. (2019) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2876179 · Cited by 166 · see citing works

Augmented Reality Maintenance Assistant Using YOLOv5

Malta, A., Mendes, M., & Farinha, T. (2021) · Applied Sciences · doi:10.3390/app11114758 · Cited by 119 · see citing works

HybridNet: A fast vehicle detection system for autonomous driving

Dai, X. (2019) · Signal Processing: Image Communication · doi:10.1016/j.image.2018.09.002 · Cited by 113 · see citing works

Deep Learning Approaches on Defect Detection in High Resolution Aerial Images of Insulators

Wen, Q., Luo, Z., Chen, R., Yang, Y., & Li, G. (2021) · Sensors · doi:10.3390/s21041033 · Cited by 110 · see citing works

Towards Real-Time Object Detection on Embedded Systems

Mao, H., Yao, S., Tang, T., Li, B., Yao, J., & Wang, Y. (2018) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2016.2593643 · Cited by 94 · see citing works

LittleYOLO-SPP: A delicate real-time vehicle detection algorithm

Sri Jamiya, S., & Rani, P. E. (2020) · Optik · doi:10.1016/j.ijleo.2020.165818 · Cited by 92 · see citing works

Improving Faster R‐CNN Framework for Fast Vehicle Detection

Nguyen, H. (2019) · Mathematical Problems in Engineering · doi:10.1155/2019/3808064 · Cited by 78 · see citing works

Prediction of Traffic Congestion Based on LSTM Through Correction of Missing Temporal and Spatial Data

Shin, D.-H., Chung, K., & Park, R. C. (2020) · IEEE Access · doi:10.1109/access.2020.3016469 · Cited by 73 · see citing works

Front Vehicle Detection Algorithm for Smart Car Based on Improved SSD Model

Cao, J., Song, C., Song, S., Peng, S., Wang, D., Shao, Y., & Xiao, F. (2020) · Sensors · doi:10.3390/s20164646 · Cited by 69 · see citing works

A CNN-Based Method of Vehicle Detection from Aerial Images Using Hard Example Mining

Koga, Y., Miyazaki, H., & Shibasaki, R. (2018) · Remote Sensing · doi:10.3390/rs10010124 · Cited by 68 · see citing works

A Robust Fabric Defect Detection Method Based on Improved RefineDet

Xie, H., & Wu, Z. (2020) · Sensors · doi:10.3390/s20154260 · Cited by 58 · see citing works

Refining Yolov4 for Vehicle DetectionPreprint

Mahto, P., Garg, P., Seth, P., & Panda, J. (2020) · SSRN Electronic Journal · Cited by 52 · see citing works

Vehicle Detection in the Aerial Infrared Images via an Improved Yolov3 Network

Zhang, X., & Zhu, X. (2019) · IEEE International Conference on Signal and Image Processing (ICSIP) · doi:10.1109/siprocess.2019.8868430 · Cited by 46 · see citing works

Vehicle detection in severe weather based on pseudo-visual search and HOG–LBP feature fusion

Wang, Z., Zhan, J., Duan, C., Guan, X., & Yang, K. (2022) · Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering · doi:10.1177/09544070211036311 · Cited by 33 · see citing works

A New Real-Time Detection and Tracking Method in Videos for Small Target Traffic Signs

Song, S., Li, Y., Huang, Q., & Li, G. (2021) · Applied Sciences · doi:10.3390/app11073061 · Cited by 27 · see citing works

Automatic pear and apple detection by videos using deep learning and a Kalman filter

Itakura, K., Narita, Y., Noaki, S., & Hosoi, F. (2021) · OSA Continuum · doi:10.1364/osac.424583 · Cited by 23 · see citing works

Heavy-Vehicle Detection Based on YOLOv4 featuring Data Augmentation and Transfer-Learning Techniques

Sowmya, V., & Radha, R. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1911/1/012029 · Cited by 15 · see citing works

Application of Transfer Learning in Infrared Pedestrian Detection

Hu, J., Zhao, Y., & Zhang, X. (2020) · IEEE International Conference on Image, Vision and Computing (ICIVC) · doi:10.1109/icivc50857.2020.9177438 · Cited by 14 · see citing works

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 · see citing works

YOLO-based lane detection system

Jeon, S.-W., Kim, D., & Jung, H. (2021) · The Journal of the Korean Institute of Information and Communication Engineering · Cited by 4 · see citing works

Vehicle tracking algorithm based on deep learning

Feng, X., Piao, Y., & Sun, S. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1920/1/012065 · Cited by 2 · see citing works

Smart Cities with Spatial Data Infrastructure and Big Data - A Critical ReviewPreprint

Kumar, S., & Jailia, M. (2018) · SSRN Electronic Journal · Cited by 2 · see citing works

Fusion of Deep Sort and Yolov5 for Effective Vehicle Detection and Tracking Scheme in Real-Time Traffic Management Sustainable System

Kumar, S., Singh, S. K., Varshney, S., Singh, S., Kumar, P., Kim, B.-G., & Ra, I.-H. (2023) · Sustainability · doi:10.3390/su152416869 · Cited by 46 · see citing works

MI-YOLO: more information based YOLO for insulator defect detection

Luan, S., Li, C., Xu, P., Huang, Y., & Wang, X. (2023) · Journal of Electronic Imaging · doi:10.1117/1.jei.32.4.043014 · Cited by 14 · see citing works

Exploring the Impact of Deep Learning Models on Lane Detection Through Semantic Segmentation

Kumar, S., Pandey, A., & Varshney, S. (2024) · SN Computer Science · doi:10.1007/s42979-023-02328-5 · Cited by 11 · see citing works

Garbage Detection using YOLO Algorithm for Urban Management in Bangkok

Panmuang, M., & Rodmorn, C. (2024) · WSEAS TRANSACTIONS ON COMPUTER RESEARCH · doi:10.37394/232018.2024.12.23 · Cited by 4 · see citing works

Implementasi Computer Vision untuk Deteksi Truk

Purnama, B., Setyorini, S., Insanudin, E., Ismail, I., Labib, F., & Furqoon, N. S. (2024) · Jurnal Pengembangan dan Pengabdian Masyarakat Multikultural · doi:10.57152/batik.v2i1.1223

NL-YOLOv5: a model with a larger receptive field and the ability to globally acquire features

Li, Z., Liu, J., Zhuo, Z., Chen, L., Zeng, X., Li, D., Zhou, Y., & Huang, C. (2026) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2026.1764856

Vehicle Detection: A Comparative Study of YOLO Models in Vehicle Detection

Lokaraj, R., Adhithiyan, B., Guruprasanna, S., & Selvam, P. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-25952-3_38

Real-time vehicle detection and computer intelligent recognition through improved YOLOv4

Ni, Z., Liu, T., Li, K., Bai, Y., & Zhu, Z. (2021) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2083/4/042006 · Cited by 6 · see citing works

LittleYOLO-SPP: A delicate real-time vehicle detection algorithm

Sri Jamiya, S., & Rani, P. E. (2020) · Optik · doi:10.1016/j.ijleo.2020.165818 · Cited by 92 · see citing works

An Efficient Algorithm for Real-Time Vehicle Detection Using Deep Neural Networks

Sri Jamiya, S. (2021) · Turkish Journal of Computer and Mathematics Education (TURCOMAT) · Cited by 5 · see citing works

Research on Vehicle Detection and Tracking Algorithm Based on Improved YOLOv5s

Xie, L., Dong, X., & Li, X. (2025) · doi:10.1109/actce66599.2025.00133

Research on Vehicle Detection Based on Deep Learning

Zhu, L., Li, X., & Xie, L. (2024) · doi:10.1109/spic62469.2024.10691464 · Cited by 1 · see citing works