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

Multi-objective deep learning for lung cancer detection in CT images: enhancements in tumor classification, localization, and diagnostic efficiency

Abdulqader, A. F., Abdulameer, S. M., Bishoyi, A. K., Yadav, A., Rekha, M. M., Kundlas, M., Kavitha, V., Aminov, Z., Abdulali, Z. S., Alwan, M., et al. (2025) · Discover Oncology · doi:10.1007/s12672-025-02314-8 · Cited by 19

A successive framework for brain tumor interpretation using Yolo variants

Priyadharshini, S., Bhoopalan, R., Manikandan, D., & Ramaswamy, K. (2025) · Scientific Reports · doi:10.1038/s41598-025-13155-4 · Cited by 19

Automated detection and quantification of leakage areas in shield tunnel linings using laser scanning data and deep learning network

Liang, H.-Y., Shen, S., Zhou, A., & Zhao, W. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111930 · Cited by 19

RA-CottNet: A Real-Time High-Precision Deep Learning Model for Cotton Boll and Flower Recognition

Wang, R.-F., Qin, Y.-M., Zhao, Y.-Y., Xu, M., Schardong, I. B., & Cui, K. (2025) · AI · doi:10.3390/ai6090235 · Cited by 23

GAN-Based Image Dehazing for Intelligent Weld Shape Classification and Tracing Using Deep Learning

Singh, A., Kalaichelvi, V., DSouza, A. S., & Karthikeyan, R. (2022) · Applied Sciences · doi:10.3390/app12146860 · Cited by 19

You Actually Look Twice At it (YALTAi): using an object detection approach instead of region segmentation within the Kraken engine

Clérice, T. (2023) · Journal of Data Mining & Digital Humanities · doi:10.46298/jdmdh.9806 · Cited by 24

Insect Detection in Sticky Trap Images of Tomato Crops Using Machine Learning

Domingues, T., Brandão, T., Ribeiro, R., & Ferreira, J. C. (2022) · Agriculture · doi:10.3390/agriculture12111967 · Cited by 22

Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm

Chen, Y., Chen, Z.-J., Lin, Y., Lin, Z., Chen, C., Yang, M., Zhang, J.-Y., Li, Y., Wang, Y., & Huang, Y.-H. (2023) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2023.1101765 · Cited by 22

PBA-YOLOv7: An Object Detection Method Based on an Improved YOLOv7 Network

Sun, Y., Li, Y., Li, S., Duan, Z., Ning, H., & Zhang, Y. (2023) · Applied Sciences · doi:10.3390/app131810436 · Cited by 23

RailSegVITNet: A lightweight VIT-based real-time track surface segmentation network for improving railroad safety

Chen, Z., Yang, J., & Zhou, F. (2024) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2024.101929 · Cited by 19

Utilizing synthetic images to enhance the automated recognition of small-sized construction tools

Han, S., Park, W., Jeong, K., Hong, T., & Koo, C. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105415 · Cited by 21

Artificial Intelligence for Routine Heritage Monitoring and Sustainable Planning of the Conservation of Historic Districts: A Case Study on Fujian Earthen Houses (Tulou)

Fan, J., Chen, Y., & Zheng, L. (2024) · Buildings · doi:10.3390/buildings14071915 · Cited by 19

Two-Stage Detection Algorithm for Plum Leaf Disease and Severity Assessment Based on Deep Learning

Yao, C., Yang, Z., Li, P., Liang, Y., Fan, Y., Luo, J., Jiang, C., & Mu, J. (2024) · Agronomy · doi:10.3390/agronomy14071589 · Cited by 19

A novel method for intelligent operation and maintenance of transformers using deep visual large model DETR + X and digital twin

Zhang, X., Sun, W., Chen, K., & Song, S. (2025) · Scientific Reports · doi:10.1038/s41598-024-83561-7 · Cited by 19

HCRP-YOLO: A lightweight algorithm for potato defect detection

Liao, H., Wang, G., Jin, S., Liu, Y., Sun, W., Yang, S., & Wang, L. (2025) · Smart Agricultural Technology · doi:10.1016/j.atech.2025.100849 · Cited by 21

Research on an Apple Recognition and Yield Estimation Model Based on the Fusion of Improved YOLOv11 and DeepSORT

Yan, Z., Wu, Y.-W., Zhao, W., Zhang, S., & Li, X. (2025) · Agriculture · doi:10.3390/agriculture15070765 · Cited by 21

Next-Generation swimming pool drowning prevention strategy integrating AI and IoT technologies

Kao, W.-C., Fan, Y., Hsu, F.-R., Shen, C.-Y., & Liao, L. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e35484 · Cited by 25

Efficient crop segmentation net and novel weed detection method

Kong, X., Liu, T., Chen, X., Jin, X., Li, A., & Yu, J. (2024) · European Journal of Agronomy · doi:10.1016/j.eja.2024.127367 · Cited by 18

EggplantDet: An efficient lightweight model for eggplant disease detection

Liu, J., & Wang, X. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2024.12.037 · Cited by 20

Enhanced hermit crabs detection using super-resolution reconstruction and improved YOLOv8 on UAV-captured imagery

Zhao, F., Chen, Y., Xi, D., Liu, Y., Wang, J., Tabeta, S., & Mizuno, K. (2025) · Marine Environmental Research · doi:10.1016/j.marenvres.2025.107313 · Cited by 18

Building construction crack detection with BCCD YOLO enhanced feature fusion and attention mechanisms

Ren, W., & Zhong, Z. (2025) · Scientific Reports · doi:10.1038/s41598-025-05665-y · Cited by 18

Advances in machine learning–enhanced microfluidic cell sorting

Li, H., Bai, J., Ma, X., Li, L., Liu, Y., Liu, X., Shen, S., & Lim, C. T. (2025) · Science Advances · doi:10.1126/sciadv.aea6007 · Cited by 19

Deep Learning in Left and Right Footprint Image Detection Based on Plantar Pressure

Ardhianto, P., Liau, B.-Y., Jan, Y., Tsai, J.-Y., Akhyar, F., Lin, C., Subiakto, R. B. R., & Lung, C.-W. (2022) · Applied Sciences · doi:10.3390/app12178885 · Cited by 18

Real-Time Human Detection for Intelligent Video Surveillance: An Empirical Research and In-depth Review of its Applications

Rani, J. U., & Raviraj, P. (2023) · SN Computer Science · doi:10.1007/s42979-022-01654-4 · Cited by 18

Nighttime Pedestrian Detection Based on a Fusion of Visual Information and Millimeter-Wave Radar

Zhao, W., Wang, T., Tan, A., & Ren, C. (2023) · IEEE Access · doi:10.1109/access.2023.3291398 · Cited by 18

Vision-Based Formation Control for an Outdoor UAV Swarm With Hierarchical Architecture

Ma, L., Meng, D., Huang, X., & Zhao, S. (2023) · IEEE Access · doi:10.1109/access.2023.3296603 · Cited by 18

Contamination Detection Using a Deep Convolutional Neural Network with Safe Machine—Environment Interaction

Hassan, S. A., Khalil, M. A., Auletta, F., Filosa, M., Camboni, D., Menciassi, A., & Oddo, C. M. (2023) · Electronics · doi:10.3390/electronics12204260 · Cited by 18

A Review on Augmented Reality and YOLO

Uma, M., Abirami, S., Ambika, M., Kavitha, M., Sureshkumar, S., & Kaviyaraj, R. (2023) · International Conference on Smart Electronics and Communication (ICOSEC) · doi:10.1109/icosec58147.2023.10275842 · Cited by 18

Tree-Level Chinese Fir Detection Using UAV RGB Imagery and YOLO-DCAM

Wang, J., Zhang, H., Liu, Y., Zhang, H., & Zheng, D. (2024) · Remote Sensing · doi:10.3390/rs16020335 · Cited by 19

Dual-Mode Learning for Multi-Dataset X-Ray Security Image Detection

Yang, F., Jiang, R., Yan, Y., Xue, J., Wang, B., & Wang, H. (2024) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2024.3364368 · Cited by 18

Enforcing Traffic Safety: A Deep Learning Approach for Detecting Motorcyclists’ Helmet Violations Using YOLOv8 and Deep Convolutional Generative Adversarial Network-Generated Images

Shoman, M., Ghoul, T., Lanzaro, G., Alsharif, T., Gargoum, S. A., & Sayed, T. (2024) · Algorithms · doi:10.3390/a17050202 · Cited by 18

Multi-Scale Semantic Map Distillation for Lightweight Pavement Crack Detection

Wang, X., Mao, Z., Liang, Z., & Shen, J. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3405477 · Cited by 23

RCYOLO: An Efficient Small Target Detector for Crack Detection in Tubular Topological Road Structures Based on Unmanned Aerial Vehicles

Dang, C., & Wang, Z. X. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3419903 · Cited by 18

MFAD-RTDETR: A Multi-Frequency Aggregate Diffusion Feature Flow Composite Model for Printed Circuit Board Defect Detection

Xie, Z., & Zou, X. (2024) · Electronics · doi:10.3390/electronics13173557 · Cited by 18

A Review on Machine Learning in Intelligent Transportation Systems Applications

Azad, A. K., Atkison, T., & Shah, A. F. M. S. (2024) · The Open Transportation Journal · doi:10.2174/0126671212330496240821114216 · Cited by 27

A systematic literature review on the role of UAV-enabled communications in advancing the UN’s sustainable development goals

Gryech, I., Vinogradov, E. A., Saboor, A., Bithas, P. S., Mathiopoulos, P. T., & Pollin, S. (2024) · Frontiers in Communications and Networks · doi:10.3389/frcmn.2024.1286073 · Cited by 18

AFM-YOLOv8s: An Accurate, Fast, and Highly Robust Model for Detection of Sporangia of Plasmopara viticola with Various Morphological Variants

Yan, C., Liang, Z., Yin, L., Wei, S., Tian, Q., Li, Y., Cheng, H., Liu, J., Yu, Q., Zhao, G., et al. (2024) · Plant Phenomics · doi:10.34133/plantphenomics.0246 · Cited by 17

Conservation in action: Cost-effective UAVs and real-time detection of the globally threatened swamp deer (Rucervus duvaucelii)

Tripathi, R. N., Agarwal, K., Tripathi, V., Badola, R., & Hussain, S. A. (2024) · Ecological Informatics · doi:10.1016/j.ecoinf.2024.102913 · Cited by 17

Comprehensive Insights into Artificial Intelligence for Dental Lesion Detection: A Systematic Review

Demir, K., SÖKMEN, Ö. Ç., Aksakalli, I. K., & AĞIRMAN, K. T. (2024) · Diagnostics · doi:10.3390/diagnostics14232768 · Cited by 17

Evaluating YOLOv4 and YOLOv5 for Enhanced Object Detection in UAV-Based Surveillance

Alhassan, M. A. M., & Yılmaz, E. (2025) · Processes · doi:10.3390/pr13010254 · Cited by 17

Efficient visual inspection of fire safety equipment in buildings

Lin, F., Wang, B., Chen, Z., Zhang, X., Song, C., Yang, L., & Cheng, J. C. P. (2025) · Automation in Construction · doi:10.1016/j.autcon.2025.105970 · Cited by 18

Binocular vision-based pose monitoring technique for assembly alignment of precast concrete components

Long, L., Guo, J., Chu, H.-H., Wang, S., Xu, S., & Deng, L. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.103205 · Cited by 17

A lightweight CNN model for UAV-based image classification

Deng, X., Shi, M., Khan, B., Choo, Y. H., Ghaffar, F., & Lim, C. P. (2025) · Soft Computing · doi:10.1007/s00500-025-10512-3 · Cited by 17

HFC-YOLO11: A Lightweight Model for the Accurate Recognition of Tiny Remote Sensing Targets

Bai, J., Zhu, W., Nie, Z., Yang, X., Qing-lin, X., & Li, D. (2025) · Computers · doi:10.3390/computers14050195 · Cited by 17

SAR ship detection across different spaceborne platforms with confusion-corrected self-training and region-aware alignment framework

Liu, S., Li, D., Song, H., Fan, C., Li, K., Wan, J., & Liu, R. (2025) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2025.07.017 · Cited by 17

YOLO in Healthcare: A Comprehensive Review of Detection Architectures, Domain Applications, and Future Innovations

Palaniappan, D., Jain, R., Premavathi, T., Parmar, K. J., Ghribi, W., Ahmed, A. M., & Ahmad, N. (2025) · IEEE Access · doi:10.1109/access.2025.3599358 · Cited by 22

Low-light multimodal object detection: A survey

Li, G., Wang, Y., He, B., Pang, T., & Gao, M. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2025.100804 · Cited by 17

SH-DETR: Enhancing steel surface defect detection and classification with an improved transformer architecture

Wu, S., Yang, H., Liao, L., Song, C., Fang, Y., & Yang, Y. (2025) · PLoS ONE · doi:10.1371/journal.pone.0334048 · Cited by 18

Performance Comparison of Various YOLO Architectures on Object Detection of UAV Images

Gunawan, T. S., Ismail, I. M. M., Kartiwi, M., & Ismail, N. (2022) · IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) · doi:10.1109/icsima55652.2022.9928938 · Cited by 18

Edge computing at sea: high-throughput classification of in-situ plankton imagery for adaptive sampling

Schmid, M. S., Daprano, D., Damle, M. M., Sullivan, C. M., Sponaugle, S., Cousin, C., Guigand, C. M., & Cowen, R. K. (2023) · Frontiers in Marine Science · doi:10.3389/fmars.2023.1187771 · Cited by 17

Microorganism Detection in Activated Sludge Microscopic Images Using Improved YOLO

Kong, Y., & Shen, Z. (2023) · Applied Sciences · doi:10.3390/app132212406 · Cited by 17

Cellphone picture-based, genus-level automated identification of Chagas disease vectors: Effects of picture orientation on the performance of five machine-learning algorithms

de Miranda, V. L., de Souza, E. P., Bambil, D. R., Khalighifar, A., Peterson, A. T., Nascimento, F. A. D. O., Gurgel‐Gonçalves, R., & Abad‐Franch, F. (2023) · Ecological Informatics · doi:10.1016/j.ecoinf.2023.102430 · Cited by 17

Guiding organs-on-chips towards applications: a balancing act between integration of advanced technologies and standardization

Meneses, J., Conceição, F., van der Meer, A. D., de Wit, S., & Teixeira, L. M. (2024) · Frontiers in Lab on a Chip Technologies · doi:10.3389/frlct.2024.1376964 · Cited by 17

The Prospect of Artificial Intelligence-Based Wood Surface Inspection: A Review

Yi, L. P., Akbar, M. F., Wahab, M. N. A., Rosdi, B. A., Fauthan, M. ‘., & Shrifan, N. H. M. M. (2024) · IEEE Access · doi:10.1109/access.2024.3412928 · Cited by 23

YOLO for Medical Object Detection (2018–2024)

Soni, A., & Rai, A. (2024) · IEEE International Conference on Electrical Power and Energy Systems (ICEPES) · doi:10.1109/icepes60647.2024.10653506 · Cited by 20

Real-time assessment of ship collision risk using image processing techniques

Ding, H., Weng, J., & Shi, K. (2024) · Applied Ocean Research · doi:10.1016/j.apor.2024.104241 · Cited by 17

Object detection in low-light conditions based on DBS-YOLOv8

Zhou, L., Dong, Y., Ma, B., Yin, Z., & Lu, F. (2024) · Cluster Computing · doi:10.1007/s10586-024-04829-1 · Cited by 20

Insulator-YOLO: Transmission Line Insulator Risk Identification Based on Improved YOLOv5

Zhang, N., Su, J., Zhao, Y., & Chen, H. (2024) · Processes · doi:10.3390/pr12112552 · Cited by 17

Environmental sensing in autonomous construction robots: Applicable technologies and systems

Okonkwo, C., & Awolusi, I. (2025) · Automation in Construction · doi:10.1016/j.autcon.2025.106075 · Cited by 17

Smoke and Fire-You Only Look Once: A Lightweight Deep Learning Model for Video Smoke and Flame Detection in Natural Scenes

Zhao, C., Zhao, L., Ka, Z., Ren, Y., Chen, H., & Sheng, Y. (2025) · Fire · doi:10.3390/fire8030104 · Cited by 21

Understanding Human Cognition Through Computational Modeling

Hsiao, J. H. (2024) · Topics in Cognitive Science · doi:10.1111/tops.12737 · Cited by 18

Research on Deep Learning Model Enhancements for PCB Surface Defect Detection

Yan, H., Zhang, H., Gao, F., Wu, H., & Tang, S. (2024) · Electronics · doi:10.3390/electronics13234626 · Cited by 16

Effective plug-and-play lightweight modules for YOLO series models

Dang, L., Li, Z., Li, S., Qiao, B., & Zhou, L. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07026-y · Cited by 16

A comprehensive review of data processing and target recognition methods for ground penetrating radar underground pipeline B-scan data

Liu, C., Li, J., Liu, Z., Tao, S., & Li, M. (2025) · Discover Applied Sciences · doi:10.1007/s42452-025-06791-y · Cited by 21

Improved you only look once for weed detection in soybean field under complex background

Zhang, W., Shi, X., Jiang, M., Zhang, A., Zeng, L., & Al‐qaness, M. A. A. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110762 · Cited by 18

An online 11 kv distribution system insulator defect detection approach with modified YOLOv11 and mobileNetV3

Bhagwat, A., Dutta, S., Saha, D., & Reddy, M. J. B. (2025) · Scientific Reports · doi:10.1038/s41598-025-99756-5 · Cited by 16

Remote Aerial Vehicle Solutions for Weed Detection in Precision Agriculture

Borah, S. S., Anand, A., Sundaravadivel, P., Fletcher, R. S., & Reddy, K. N. (2025) · IEEE Access · doi:10.1109/access.2025.3575601 · Cited by 18

Improved YOLOv8 framework for efficient solar panel defect detection

Batool, A., Kim, Y.-W., & Byun, Y.-C. (2025) · Journal of Building Engineering · doi:10.1016/j.jobe.2025.113031 · Cited by 17

Deep Learning for Fluorescence Lifetime Predictions Enables High-Throughput In Vivo Imaging

Kapsiani, S., Läubli, N. F., Ward, E., Fernández‐Villegas, A., Mazumder, B., Kaminski, C. F., & Schierle, G. S. K. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.5c03749 · Cited by 20

DMF-YOLO: Dynamic Multi-Scale Feature Fusion Network-Driven Small Target Detection in UAV Aerial Images

Yan, X., Sun, S., Zhu, H., Hu, Q., Ying, W., & Li, Y. (2025) · Remote Sensing · doi:10.3390/rs17142385 · Cited by 17

Deep learning and digital twin integration for structural damage detection in ancient pagodas

Xu, S., & Chen, H. (2025) · Scientific Reports · doi:10.1038/s41598-025-14029-5 · Cited by 17

Cherry Tomato Bunch and Picking Point Detection for Robotic Harvesting Using an RGB-D Sensor and a StarBL-YOLO Network

Li, P., Wen, M., Zeng, Z., & Tian, Y. (2025) · Horticulturae · doi:10.3390/horticulturae11080949 · Cited by 16

SD-YOLOv5: a rapid detection method for personal protective equipment on construction sites

Li, C., Wang, J., Luo, B., Yin, T., Liu, B., & Lu, J. (2025) · Frontiers in Built Environment · doi:10.3389/fbuil.2025.1563483 · Cited by 16

An adaptive focused target feature fusion network for detection of foreign bodies in coal flow

Tao, Y., Zheng, Z., Li, Y., Zhang, X., Deng, X., Ouyang, Y., Zhao, Z., & Gao, X.-Z. (2023) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-023-01798-6 · Cited by 16

Strategies for Improving Object Detection in Real-Time Projects that use Deep Learning Technology

Abed, N., & Ramu, M. (2023) · IEEE International Conference for Convergence in Technology (I2CT) · doi:10.1109/i2ct57861.2023.10126449 · Cited by 16

Enhanced Food Classification System Using YOLO Models For Object Detection Algorithm

Sudharson, S., Kokil, P., Annamalai, R., & Manoj, N. V. S. (2023) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt56998.2023.10307943 · Cited by 16

Metastatic Lymph Node Detection on Ultrasound Images Using YOLOv7 in Patients with Head and Neck Squamous Cell Carcinoma

Eida, S., Fukuda, M., Katayama, I., Takagi, Y., Sasaki, M., Mori, H., Kawakami, M., Nishino, T., Ariji, Y., & Sumi, M. (2024) · Cancers · doi:10.3390/cancers16020274 · Cited by 16

Real-Time People Counting System using YOLOv8 Object Detection

Elaoua, A., Nadour, M., Cherroun, L., & Elasri, A. (2023) · International Conference on Electronics, Energy and Measurement (IC2EM) · doi:10.1109/ic2em59347.2023.10419684 · Cited by 16

Validating the Use of Smart Glasses in Industrial Quality Control: A Case Study

da Silva, J. P. L. R., Coelho, P., Saraiva, L., Váz, P., Martins, P., & Henriques, J. (2024) · Applied Sciences · doi:10.3390/app14051850 · Cited by 38

Redefining Age-Friendly Neighbourhoods: Translating the Promises of Blue Zones for Contemporary Urban Environments

Najafi, P., & Mohammadi, M. (2024) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph21030365 · Cited by 16

vEpiNet: A multimodal interictal epileptiform discharge detection method based on video and electroencephalogram data

Lin, N., Gao, W., Li, L., Chen, J., Liang, Z., Yuan, G., Sun, H., Liu, Q., Chen, J., Jin, L., et al. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106319 · Cited by 18

Performance Comparison of Cherry Tomato Ripeness Detection Using Multiple YOLO Models

Yang, D., & Ju, C. (2024) · AgriEngineering · doi:10.3390/agriengineering7010008 · Cited by 17

Visual localization with a monocular camera for unmanned aerial vehicle based on landmark detection and tracking using YOLOv5 and DeepSORT

Ma, L., Meng, D., Zhao, S., & An, B. (2023) · International Journal of Advanced Robotic Systems · doi:10.1177/17298806231164831 · Cited by 18

A fine-grained dataset for sewage outfalls objective detection in natural environments

Tian, Y., Deng, N., Xu, J., & Wen, Z. (2024) · Scientific Data · doi:10.1038/s41597-024-03574-9 · Cited by 16

Enhancing Microcalcification Detection in Mammography with YOLO-v8 Performance and Clinical Implications

Shia, W.-C., & Ku, T.-H. (2024) · Diagnostics · doi:10.3390/diagnostics14242875 · Cited by 16

Tiny deep learning model for insect segmentation and counting on resource-constrained devices

Kargar, A., Zorbas, D., Gaffney, M., O’Flynn, B., & Tedesco, S. A. (2025) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2025.110378 · Cited by 15

Review on crack detection in civil infrastructure using structural health monitoring and machine learning techniques

Khan, M. Z., Shahzadi, M., Khan, A. A., Ali, U. A., Hassan, M. A. S., & Hussain, M. (2025) · Innovative Infrastructure Solutions · doi:10.1007/s41062-025-02147-y · Cited by 24

PCPE-YOLO with a lightweight dynamically reconfigurable backbone for small object detection

Chen, W., Liu, J., Liu, T., & Zhuang, Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-15975-w · Cited by 18

Education robot object detection with a brain-inspired approach integrating Faster R-CNN, YOLOv3, and semi-supervised learning

Hong, Q., Dong, H., Deng, W., & Ping, Y. (2024) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2023.1338104 · Cited by 15

Addressing Ergonomic Challenges in Agriculture through AI-Enabled Posture Classification

Kapse, S., Wu, R., & Thamsuwan, O. (2024) · Applied Sciences · doi:10.3390/app14020525 · Cited by 17

Performance evaluation of a deep learning model for automatic detection and localization of idiopathic osteosclerosis on dental panoramic radiographs

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