A Review of Yolo Algorithm Developments

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

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

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

Apple detection during different growth stages in orchards using the improved YOLO-V3 model

Tian, Y., Yang, G., Wang, Z., Wang, H., Li, E., & Liang, Z. (2019) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2019.01.012 · Cited by 1,043

A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector

Laroca, R., Severo, E. B., Junior, L. A. Z., Oliveira, L. S., Gonçalves, G. R., Schwartz, W. R., & Menotti, D. (2018) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2018.8489629 · Cited by 670

YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers

Huang, R., Pedoeem, J., & Chen, C. (2018) · 2018 IEEE International Conference on Big Data (Big Data) · doi:10.1109/bigdata.2018.8621865 · Cited by 622

A Review of Object Detection Models Based on Convolutional Neural Network

Sultana, F., Sufian, A., & Dutta, P. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-981-15-4288-6_1 · Cited by 327

A review of object detection based on convolutional neural network

Wang, Z., & Liu, J. (2017) · Chinese Control Conference (CCC) · doi:10.23919/chicc.2017.8029130 · Cited by 268

A YOLO-Based Traffic Counting System

Lin, J., & Sun, M.-T. (2018) · Conference on Technologies and Applications of Artificial Intelligence (TAAI) · doi:10.1109/taai.2018.00027 · Cited by 116

A Vehicle Detection Method for Aerial Image Based on YOLO

Lu, J., Ma, C., Li, L., Xing, X., Zhang, Y., Wang, Z., & Xu, J. (2018) · Journal of Computer and Communications · doi:10.4236/jcc.2018.611009 · Cited by 101

YOLOv8: A Novel Object Detection Algorithm with Enhanced Performance and Robustness

Varghese, R., & M., S. (2024) · 2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS) · doi:10.1109/adics58448.2024.10533619 · Cited by 2,007

YOLOv1 to v8: Unveiling Each Variant–A Comprehensive Review of YOLO

Hussain, M. (2024) · IEEE Access · doi:10.1109/access.2024.3378568 · Cited by 492

YOLO advances to its genesis: a decadal and comprehensive review of the You Only Look Once (YOLO) series

Sapkota, R., Flores-Calero, M., Qureshi, R., Badjugar, C., Nepal, U., Poulose, A., Zeno, P. J., Vaddevolu, U. B. P., Khan, S., Shoman, M., et al. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11253-3 · Cited by 507

A Lightweight YOLOv8 Tomato Detection Algorithm Combining Feature Enhancement and Attention

Yang, G., Wang, J., Nie, Z., Yang, H., & Yu, S. (2023) · Agronomy · doi:10.3390/agronomy13071824 · Cited by 323

A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023)

Ragab, M. G., Abdulkadir, S. J., Muneer, A., Alqushaibi, A., Sumiea, E. H., Qureshi, R., Al-Selwi, S. M., & Alhussian, H. (2024) · IEEE Access · doi:10.1109/access.2024.3386826 · Cited by 306

Small-object detection based on YOLOv5 in autonomous driving systems

Mahaur, B., & Mishra, K. K. (2023) · Pattern Recognition Letters · doi:10.1016/j.patrec.2023.03.009 · Cited by 277

A Comprehensive Review of Convolutional Neural Networks for Defect Detection in Industrial Applications

Khanam, R., Hussain, M., Hill, R. C., & Allen, P. (2024) · IEEE Access · doi:10.1109/access.2024.3425166 · Cited by 296

Tea leaf disease detection and identification based on YOLOv7 (YOLO-T)

Soeb, M. J. A., Jubayer, M. F., Tarin, T. A., Mamun, M. R. A., Ruhad, F. M., Parven, A., Mubarak, N. M., Karri, S. L., & Meftaul, I. M. (2023) · Scientific Reports · doi:10.1038/s41598-023-33270-4 · Cited by 237

Advancements and Challenges in Machine Learning: A Comprehensive Review of Models, Libraries, Applications, and Algorithms

Tufail, S., Riggs, H., Tariq, M., & Sarwat, A. I. (2023) · Electronics · doi:10.3390/electronics12081789 · Cited by 267

Statistical Analysis of Design Aspects of Various YOLO-Based Deep Learning Models for Object Detection

Sirisha, U., Praveen, S. P., Srinivasu, P. N., Barsocchi, P., & Bhoi, A. K. (2023) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-023-00302-w · Cited by 274

YOLO-Based UAV Technology: A Review of the Research and Its Applications

Chen, C., Zheng, Z., Xu, T., Guo, S., Feng, S., Yao, W., & Lan, Y. (2023) · Drones · doi:10.3390/drones7030190 · Cited by 223

YOLOv8-QSD: An Improved Small Object Detection Algorithm for Autonomous Vehicles Based on YOLOv8

Wang, H., Liu, C., Cai, Y., Chen, L., & Li, Y. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3379090 · Cited by 218

Automated Brain Tumor Segmentation and Classification in MRI Using YOLO-Based Deep Learning

Almufareh, M. F., Imran, M., Khan, A., Humayun, M., & Asim, M. F. (2024) · IEEE Access · doi:10.1109/access.2024.3359418 · Cited by 218

A Review of Practical AI for Remote Sensing in Earth Sciences

Janga, B., Asamani, G. P., Sun, Z., & Cristea, N. C. (2023) · Remote Sensing · doi:10.3390/rs15164112 · Cited by 244

Improved YOLOv5: Efficient Object Detection Using Drone Images under Various Conditions

Jung, H.-K., & Choi, G.-S. (2022) · Applied Sciences · doi:10.3390/app12147255 · Cited by 200

Traffic Sign Detection and Recognition Using YOLO Object Detection Algorithm: A Systematic Review

Flores-Calero, M. J., Astudillo, C. A., Guevara, D., Maza, J., Lita, B. S., Defaz, B., Ante, J. S., Zabala‐Blanco, D., & Armingol, J. M. (2024) · Mathematics · doi:10.3390/math12020297 · Cited by 206

GBH-YOLOv5: Ghost Convolution with BottleneckCSP and Tiny Target Prediction Head Incorporating YOLOv5 for PV Panel Defect Detection

Li, L., Wang, Z., & Zhang, T. (2023) · Electronics · doi:10.3390/electronics12030561 · Cited by 167

Lightweight object detection algorithm for robots with improved YOLOv5

Liu, G., Hu, Y., Chen, Z., Guo, J., & Ni, P. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.106217 · Cited by 158

An improved algorithm for small object detection based on YOLO v4 and multi-scale contextual information

Ji, S.-J., Ling, Q.-H., & Han, F. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108490 · Cited by 150

NAS-YOLOX: a SAR ship detection using neural architecture search and multi-scale attention

Wang, H., Han, D., Cui, M., & Chen, C. (2023) · Connection Science · doi:10.1080/09540091.2023.2257399 · Cited by 147

Nonlinear and threshold effects of the built environment, road vehicles and air pollution on urban vitality

Doan, Q. C., Ma, J., Chen, S., & Zhang, X. (2024) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2024.105204 · Cited by 131

Object Detection in Adverse Weather for Autonomous Driving through Data Merging and YOLOv8

Kumar, D., & Muhammad, N. (2023) · Sensors · doi:10.3390/s23208471 · Cited by 135

A mobile-based system for maize plant leaf disease detection and classification using deep learning

Khan, F., Zafar, N., Tahir, M. N., Aqib, M., Waheed, H., & Haroon, Z. (2023) · Frontiers in Plant Science · doi:10.3389/fpls.2023.1079366 · Cited by 147

In-Depth Review of YOLOv1 to YOLOv10 Variants for Enhanced Photovoltaic Defect Detection

Hussain, M., & Khanam, R. (2024) · Solar · doi:10.3390/solar4030016 · Cited by 129

Using lightweight deep learning algorithm for real-time detection of apple flowers in natural environments

Shang, Y., Xu, X., Jiao, Y., Wang, Z., Hua, Z., & Song, H. (2023) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2023.107765 · Cited by 104

Utilizing YOLOv8 for enhanced traffic monitoring in intelligent transportation systems (ITS) applications

Bakırcı, M. (2024) · Digital Signal Processing · doi:10.1016/j.dsp.2024.104594 · Cited by 98

A systematic literature review of defect detection in railways using machine vision-based inspection methods

Kumar, A., & Harsha, S. P. (2024) · International Journal of Transportation Science and Technology · doi:10.1016/j.ijtst.2024.06.006 · Cited by 111

UAV Target Detection Algorithm Based on Improved YOLOv8

Wang, F., Wang, H., Qin, Z., & Tang, J. (2023) · IEEE Access · doi:10.1109/access.2023.3325677 · Cited by 99

A performance comparison of YOLOv8 models for traffic sign detection in the Robotaxi-full scale autonomous vehicle competition

Soylu, E., & Soylu, T. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16451-1 · Cited by 88

Basketball action recognition based on the combination of YOLO and a deep fuzzy LSTM network

Khobdeh, S. B., Yamaghani, M. R., & Khodaparast, S. (2023) · The Journal of Supercomputing · doi:10.1007/s11227-023-05611-7 · Cited by 90

Enhancing automated vehicle identification by integrating YOLO v8 and OCR techniques for high-precision license plate detection and recognition

Moussaoui, H., Akkad, N. E., Benslimane, M., El‐Shafai, W., Baihan, A., Hewage, C. T. E. R., & Rathore, R. S. (2024) · Scientific Reports · doi:10.1038/s41598-024-65272-1 · Cited by 83

An Improved YOLOv8 Algorithm for Rail Surface Defect Detection

Wang, Y., Zhang, K., Wang, L., & Wu, L. (2024) · IEEE Access · doi:10.1109/access.2024.3380009 · Cited by 82

Automated detection and segmentation of tunnel defects and objects using YOLOv8-CM

Zhang, C., Chen, X., Liu, P., He, B., Li, W., & Song, T. (2024) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2024.105857 · Cited by 78

Advancing precision agriculture: The potential of deep learning for cereal plant head detection

Sanaeifar, A., Guindo, M. L., Bakhshipour, A., Fazayeli, H., Li, X., & Yang, C. (2023) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2023.107875 · Cited by 81

Latent-KalmanNet: Learned Kalman Filtering for Tracking From High-Dimensional Signals

Buchnik, I., Revach, G., Steger, D., van Sloun, R. J. G., Routtenberg, T., & Shlezinger, N. (2023) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2023.3344360 · Cited by 76

Detection of Pine Wilt Disease Using AAV Remote Sensing With an Improved YOLO Model

Wang, L., Cai, J., Wang, T., Zhao, J., Gadekallu, T. R., & Fang, K. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3478333 · Cited by 78

RailFOD23: A dataset for foreign object detection on railroad transmission lines

Chen, Z., Yang, J., Feng, Z., & Zhu, H. (2024) · Scientific Data · doi:10.1038/s41597-024-02918-9 · Cited by 77

LS-YOLO: A Novel Model for Detecting Multiscale Landslides With Remote Sensing Images

Zhang, W., Liu, Z., Zhou, S., Qi, W., Wu, X., Zhang, T., & Han, L. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3363160 · Cited by 81

Sweet potato leaf detection in a natural scene based on faster R-CNN with a visual attention mechanism and DIoU-NMS

Wang, M., Fu, B., Fan, J., Wang, Y., Zhang, L., & Xia, C. (2022) · Ecological Informatics · doi:10.1016/j.ecoinf.2022.101931 · Cited by 76

Analyzing Real-Time Object Detection with YOLO Algorithm in Automotive Applications: A Review

Gheorghe, C., Duguleană, M., Boboc, R. G., & Postelnicu, C. (2024) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2024.054735 · Cited by 84

Aero-Engine Blade Defect Detection: A Systematic Review of Deep Learning Models

Abdulrahman, Y., Eltoum, M. A. M., Ayyad, A., Moyo, B., & Zweiri, Y. (2023) · IEEE Access · doi:10.1109/access.2023.3280992 · Cited by 74

Cardiac Healthcare Digital Twins Supported by Artificial Intelligence-Based Algorithms and Extended Reality—A Systematic Review

Rudnicka, Z., Proniewska, K. K., Perkins, M. D., & Pręgowska, A. (2024) · Electronics · doi:10.3390/electronics13050866 · Cited by 70

SerpensGate-YOLOv8: an enhanced YOLOv8 model for accurate plant disease detection

Miao, Y., Meng, W., & Zhou, X. (2025) · Frontiers in Plant Science · doi:10.3389/fpls.2024.1514832 · Cited by 70

Underwater Target Detection Using Deep Learning: Methodologies, Challenges, Applications, and Future Evolution

Khan, A., Fouda, M. M., Do, D., Almaleh, A., Alqahtani, A. M., & Rahman, A. U. (2024) · IEEE Access · doi:10.1109/access.2024.3353688 · Cited by 68

Construction Site Hazards Identification Using Deep Learning and Computer Vision

Alateeq, M. M., P., F. R. P., & Ali, M. A. S. (2023) · Sustainability · doi:10.3390/su15032358 · Cited by 89

Sensor-Fusion Based Navigation for Autonomous Mobile Robot

Ušinskis, V., Nowicki, M., Dzedzickis, A., & Bučinskas, V. (2025) · Sensors · doi:10.3390/s25041248 · Cited by 67

Fuzzy Logic with Deep Learning for Detection of Skin Cancer

Singh, S. K., Abolghasemi, V., & Anisi, M. H. (2023) · Applied Sciences · doi:10.3390/app13158927 · Cited by 68

Computer vision-based safety risk computing and visualization on construction sites

Hou, X., Li, C., & Fang, Q. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.105129 · Cited by 66

Autonomous UAV navigation using deep learning-based computer vision frameworks: A systematic literature review

Katkuri, A. V. R., Madan, H., Khatri, N., Abdul-Qawy, A. S. H., & Patnaik, K. S. (2024) · Array · doi:10.1016/j.array.2024.100361 · Cited by 66

Real-Time Personal Protective Equipment Compliance Detection Based on Deep Learning Algorithm

Lo, J.-H., Lin, L.-K., & Hung, C.-C. (2022) · Sustainability · doi:10.3390/su15010391 · Cited by 81

Robust Classification and Detection of Big Medical Data Using Advanced Parallel K-Means Clustering, YOLOv4, and Logistic Regression

Awad, F. H., Hamad, M. M., & Alzubaidi, L. (2023) · Life · doi:10.3390/life13030691 · Cited by 67

Image annotation and curation in radiology: an overview for machine learning practitioners

Galbusera, F., & Cina, A. (2024) · European Radiology Experimental · doi:10.1186/s41747-023-00408-y · Cited by 62

Detection of powdery mildew on strawberry leaves based on DAC-YOLOv4 model

Li, Y., Wang, J., Wu, H., Yu, Y. F., Sun, H., & Zhang, H. (2022) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2022.107418 · Cited by 61

Solar panel defect detection design based on YOLO v5 algorithm

Huang, J., Zeng, K., Zhang, Z., & Zhong, W. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e18826 · Cited by 70

Vehicle-Road-Cloud Collaborative Perception Framework and Key Technologies: A Review

Gao, B., Liu, J., Zou, H., Chen, J., He, L., & Li, K. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3459799 · Cited by 65

Two Novel Models for Traffic Sign Detection Based on YOLOv5s

Bai, W., Zhao, J., Dai, C., Zhang, H., Zhao, L., Ji, Z., & Ганчев, И. (2023) · Axioms · doi:10.3390/axioms12020160 · Cited by 59

Weighted Pseudo-Labels and Bounding Boxes for Semisupervised SAR Target Detection

Tian, Z., Wang, W., Zhou, K., Song, X., Shen, Y., & Liu, S. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3363491 · Cited by 67

PODB: A learning-based polarimetric object detection benchmark for road scenes in adverse weather conditions

Zhu, Z., Li, X., Zhai, J., & Hu, H. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102385 · Cited by 60

Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans

Zafar, W., Husnain, G., Iqbal, A., Alzahrani, A. S., Irfan, M. A., Ghadi, Y. Y., Alzahrani, M. S., & Naidu, R. S. (2024) · Results in Engineering · doi:10.1016/j.rineng.2024.102994 · Cited by 66

An efficient automated vehicle license plate recognition system under image processing

Islam, D., Mahmud, T., & Chowdhury, T. (2022) · Indonesian Journal of Electrical Engineering and Computer Science · doi:10.11591/ijeecs.v29.i2.pp1055-1062 · Cited by 56

Edge AI in Practice: A Survey and Deployment Framework for Neural Networks on Embedded Systems

Cordova-Cardenas, R., Amor, D., & Gutiérrez, Á. (2025) · Electronics · doi:10.3390/electronics14244877 · Cited by 67

Lightweight You Only Look Once v8: An Upgraded You Only Look Once v8 Algorithm for Small Object Identification in Unmanned Aerial Vehicle Images

Huangfu, Z., & Li, S. (2023) · Applied Sciences · doi:10.3390/app132212369 · Cited by 61

YOLOv7-RDD: A Lightweight Efficient Pavement Distress Detection Model

Ning, Z., Wang, H., Li, S., & Xu, Z. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3347034 · Cited by 58

Tracking and monitoring of individual pig behavior based on YOLOv5-Byte

Tu, S., Cai, Y., Liang, Y., Lei, H., Huang, Y., Liu, H., & Xiao, D. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.108997 · Cited by 56

Automatic object detection for behavioural research using YOLOv8

Hermens, F. (2024) · Behavior Research Methods · doi:10.3758/s13428-024-02420-5 · Cited by 71

A systematic review of UAV and AI integration for targeted disease detection, weed management, and pest control in precision agriculture

Anam, I., Arafat, N., Hafiz, M. S., Jim, J. R., Kabir, M. M., & Mridha, M. F. (2024) · Smart Agricultural Technology · doi:10.1016/j.atech.2024.100647 · Cited by 72

A Study of YOLO Architectures for Wildfire and Smoke Detection in Ground and Aerial Imagery

Ramos, L., Casas, E., Romero, C., Rivas-Echeverría, F., & Bendek, E. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.104869 · Cited by 64

Improved Field-Based Soybean Seed Counting and Localization with Feature Level Considered

Zhao, J., Kaga, A., Yamada, T., Komatsu, K., Hirata, K., Kikuchi, A., Hirafuji, M., Ninomiya, S., & Guo, W. (2023) · Plant Phenomics · doi:10.34133/plantphenomics.0026 · Cited by 54

Efficient railway track region segmentation algorithm based on lightweight neural network and cross-fusion decoder

Chen, Z., Yang, J., Chen, L., Feng, Z., & Jia, L. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.105069 · Cited by 53

A streamlined approach for intelligent ship object detection using EL-YOLO algorithm

Yang, D., Solihin, M. I., Ardiyanto, I., Zhao, Y., Li, W., Cai, B., & Chen, C. (2024) · Scientific Reports · doi:10.1038/s41598-024-64225-y · Cited by 61

Real-Time Detection of Microplastics Using an AI Camera

Sarker, M. A. B., Imtiaz, M. H., Holsen, T. M., & Baki, A. B. M. (2024) · Sensors · doi:10.3390/s24134394 · Cited by 62

Multi-Object Detection for Daily Road Maintenance Inspection With UAV Based on Improved YOLOv8

Zhu, J., Wu, Y., & Ma, T. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3437770 · Cited by 60

Enhanced Self-Checkout System for Retail Based on Improved YOLOv10

Tan, L., Liu, S., Gao, J., Liu, X., Chu, L., & Jiang, H. (2024) · Journal of Imaging · doi:10.3390/jimaging10100248 · Cited by 53

Object Detection for Construction Waste Based on an Improved YOLOv5 Model

Zhou, Q., Liu, H., Qiu, Y., & Zheng, W. (2022) · Sustainability · doi:10.3390/su15010681 · Cited by 52

Railway obstacle intrusion warning mechanism integrating YOLO-based detection and risk assessment

Zhang, Z., Chen, P., Huang, Y., Dai, L., Xu, F., & Hu, H. (2024) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2024.100571 · Cited by 52

YOLO deep learning algorithm for object detection in agriculture: a review

Kamalesh Kanna, S., Kumaraperumal, R., Pazhanivelan, P., Jagadeeswaran, R., & Prabu, P. C. (2024) · Journal of Agricultural Engineering · doi:10.4081/jae.2024.1641 · Cited by 65

Deep Learning for Tomato Disease Detection with YOLOv8

Zayani, H. M., Ammar, I., Ghodhbani, R., Maqbool, A., Saidani, T. S., Slimane, J. B., Kachoukh, A., Kouki, M., Kallel, M., Alsuwaylimi, A. A., et al. (2024) · Engineering Technology & Applied Science Research · doi:10.48084/etasr.7064 · Cited by 51

Methods for Detecting and Classifying Weeds, Diseases and Fruits Using AI to Improve the Sustainability of Agricultural Crops: A Review

Corceiro, A., Alibabaei, K., Assunção, E., Gaspar, P. D., & Pereira, N. J. M. (2023) · Processes · doi:10.3390/pr11041263 · Cited by 50

Hyper-parameter tuned deep learning approach for effective human monkeypox disease detection

Dahiya, N., Sharma, Y. K., Rani, U., V, Hussain, S., Khan, V., Mohan, A., & Nuristani, N. (2023) · Scientific Reports · doi:10.1038/s41598-023-43236-1 · Cited by 50

Identification of cotton pest and disease based on CFNet- VoV-GCSP -LSKNet-YOLOv8s: a new era of precision agriculture

Li, R., He, Y., Li, Y., Qin, W., Abbas, A., Ji, R., Li, S., Wu, Y., Sun, X., & Yang, J. (2024) · Frontiers in Plant Science · doi:10.3389/fpls.2024.1348402 · Cited by 50

Mislaying behavior detection in cage-free hens with deep learning technologies

Bist, R. B., Yang, X. Y., Subedi, S., & Chai, L. (2023) · Poultry Science · doi:10.1016/j.psj.2023.102729 · Cited by 52

A Real-Time Defect Detection Strategy for Additive Manufacturing Processes Based on Deep Learning and Machine Vision Technologies

Wang, W., Wang, P., Zhang, H., Chen, X., Wang, G., Lu, Y., Chen, M., Liu, H., & Li, J. (2023) · Micromachines · doi:10.3390/mi15010028 · Cited by 55

A Review on Automated Detection and Assessment of Fruit Damage Using Machine Learning

Yonasi, S., Nabende, J. N., Nakasi, R., & Nakibuule, R. (2024) · IEEE Access · doi:10.1109/access.2024.3362230 · Cited by 49

Rose-Mamba-YOLO: an enhanced framework for efficient and accurate greenhouse rose monitoring

You, S., Li, B., Chen, Y., Ren, Z., Liu, Y., Wu, Q., Tao, J., Zhang, Z., Zhang, C., Xue, F., et al. (2025) · Frontiers in Plant Science · doi:10.3389/fpls.2025.1607582 · Cited by 51

Fish Detection and Classification for Automatic Sorting System with an Optimized YOLO Algorithm

Kuswantori, A., Suesut, T., Tangsrirat, W., Schleining, G., & Nunak, N. (2023) · Applied Sciences · doi:10.3390/app13063812 · Cited by 48

Opportunities and challenges for deep learning in cell dynamics research

Chai, B., Efstathiou, C., Yue, H., & Draviam, V. M. (2023) · Trends in Cell Biology · doi:10.1016/j.tcb.2023.10.010 · Cited by 56

YOLOv8-ACCW: Lightweight Grape Leaf Disease Detection Method Based on Improved YOLOv8

Chen, Z., Feng, J., Zhu, K., Yang, Z., Wang, Y., & Ren, M. (2024) · IEEE Access · doi:10.1109/access.2024.3453379 · Cited by 48

Advancing crop health with YOLOv11 classification of plant diseases

Eliwa, E. H. I., & El‐Hafeez, T. A. (2025) · Neural Computing and Applications · doi:10.1007/s00521-025-11287-2 · Cited by 48

A Review of YOLO Algorithm and Its Applications in Autonomous Driving Object Detection

Wei, J., As’arry, A., Rezali, K. A. M., Yusoff, M. Z. M., Ma, H., & Zhang, K.-L. (2025) · IEEE Access · doi:10.1109/access.2025.3573376 · Cited by 67

Hypertuned-YOLO for interpretable distribution power grid fault location based on EigenCAM

Stefenon, S. F., Seman, L. O., Klaar, A. C. R., Ovejero, R. G., & Leithardt, V. R. Q. (2024) · Ain Shams Engineering Journal · doi:10.1016/j.asej.2024.102722 · Cited by 47

A survey of video-based human action recognition in team sports

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