Revisiting RCNN: On Awakening the Classification Power of Faster RCNN

Deep Residual Learning for Image Recognition

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

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ImageNet: A large-scale hierarchical image database

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

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Microsoft COCO: Common Objects in Context

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Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

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Feature Pyramid Networks for Object Detection

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Focal Loss for Dense Object Detection

Lin, T.-Y., Goyal, P., Girshick, R., He, K., & Dollar, P. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.324 · Cited by 30,581

Mask R-CNN

He, K., Gkioxari, G., Dollar, P., & Girshick, R. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.322 · Cited by 29,137

Towards improving classification power for one-shot object detection

Yang, H., Lin, Y., Zhang, H., Zhang, Y., & Xu, B. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.04.116 · Cited by 20

Deep Learning-Based Multi-object Tracking

Kumar, A., Sareen, P., & Raja (2023) · Contributions to environmental sciences & innovative business technology · doi:10.1007/978-981-99-3288-7_8 · Cited by 18

CONet: Crowd and occlusion-aware network for occluded human pose estimation

Bai, X., Wei, X., Wang, Z., & Zhang, M. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106109 · Cited by 18

A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and DatasetsPreprint

Muzammul, M., & Li, X. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.07927 · Cited by 19

ForkNet: Overlapping Image Disentanglement for Accurate Prohibited Item Detection

Jia, T., Ma, B., Wang, H., Li, M., Lin, S., & Chen, D. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3394483 · Cited by 17

A comparison of deep learning algorithms on image data for detecting floodwater on roadways

Sarp, S., Kuzlu, M., Zhao, Y., Cetin, M., & Güler, Ö. (2021) · Computer Science and Information Systems · doi:10.2298/csis210313058s · Cited by 17

Fully Cascade Consistency Learning for One-Stage Object Detection

Wang, H., Jia, T., Ma, B., Wang, Q., & Zuo, W. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3263557 · Cited by 17

Location-Aware Box Reasoning for Anchor-Based Single-Shot Object Detection

Ma, W., Li, K., & Wang, G. (2020) · IEEE Access · doi:10.1109/access.2020.3009344 · Cited by 17

Group Sampling for Scale Invariant Face Detection

Xiang, M., Wei, F., Zhang, T., Chen, D., Zheng, N., & Wen, F. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3012414 · Cited by 17

CPM R-CNN: Calibrating Point-guided Misalignment in Object Detection

Zhu, B., Song, Q., Yang, L., Wang, Z., Liu, C., & Hu, M. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00329 · Cited by 17

CRACT: Cascaded Regression-Align-Classification for Robust Tracking

Fan, H., & Ling, H. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9636803 · Cited by 17

OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillationPreprint

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2D Object Detection: A Survey

Malagoli, E., & Persio, L. D. (2025) · Mathematics · doi:10.3390/math13060893 · Cited by 19

Scalable Multi-grained Cross-modal Similarity Query with Interpretability

Zhu, M., Shen, D., Lixin, X., & Wang, X. (2021) · Data Science and Engineering · doi:10.1007/s41019-021-00162-4 · 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

Infrared image detection of defects in lightweight solar panels based on improved MSRCR and YOLOv8n

Hong, Y., Pan, R., Su, J., & Li, M. (2024) · Infrared Physics & Technology · doi:10.1016/j.infrared.2024.105473 · Cited by 16

BoxMask: Revisiting Bounding Box Supervision for Video Object Detection

Hashmi, K. A., Pagani, A., Stricker, D., & Afzal, M. Z. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00207 · Cited by 16

Utilizing the Instability in Weakly Supervised Object DetectionPreprint

Gao, Y., Liu, B., Guo, N., Ye, X., Wan, F., You, H., & Fan, D. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.06023 · Cited by 16

Real-Time Detection of Crops with Dense Planting Using Deep Learning at Seedling Stage

Kong, S., Li, J., Zhai, Y., Gao, Z., Zhou, Y., & Xu, Y. (2023) · Agronomy · doi:10.3390/agronomy13061503 · Cited by 15

Toward High-Accuracy and Real-Time Two-Stage Small Object Detection on FPGA

Li, S., Zhu, Z., Sun, H., Ning, X., Dai, G., Hu, Y., Yang, H., & Wang, Y. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3385121 · Cited by 16

Lightweight Tomato Leaf Intelligent Disease Detection Model Based on Adaptive Kernel Convolution and Feature Fusion

Ji, B., Li, H., Jin, X., Zhang, J., Tao, F., Li, P., Wang, J., & Fan, H. (2024) · IEEE Transactions on AgriFood Electronics · doi:10.1109/tafe.2024.3445119 · Cited by 15

Visual Object Recognition in Indoor Environments Using Topologically Persistent Features

Samani, E. U., Yang, X., & Banerjee, A. G. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3099460 · Cited by 16

Improved Faster RCNN for Traffic Sign Detection

Wang, F., Li, Y., Wei, Y., & Dong, H. (2020) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc45102.2020.9294270 · Cited by 15

GeminiNet: Combine Fully Convolution Network With Structure of Receptive Fields for Object Detection

Yao, S., Chen, Y., Tian, X., & Jiang, R. (2020) · IEEE Access · doi:10.1109/access.2020.2982939 · Cited by 15

Hierarchical Multi-Label Object Detection Framework for Remote Sensing Images

Shin, S., Kim, S.-Y., Kim, Y., & Kim, S. (2020) · Remote Sensing · doi:10.3390/rs12172734 · Cited by 15

Surgical Tools Detection Based on Training Sample Adaptation in Laparoscopic Videos

Wang, G.-Y., & Wang, S. (2020) · IEEE Access · doi:10.1109/access.2020.3028910 · Cited by 14

Automatic Detection of Transformer Components in Inspection Images Based on Improved Faster R-CNN

Liu, Z., & Wang, H. (2018) · Energies · doi:10.3390/en11123496 · Cited by 14

LIP: Local Importance-Based Pooling

Gao, Z., Wang, L., & Wu, G. (2022) · International Journal of Computer Vision · doi:10.1007/s11263-022-01707-4 · Cited by 15

Learning Critical Features for Arbitrary-Oriented Object Detection in Remote-Sensing Optical Images

Sun, P., Zheng, Y., Wu, W., Xu, W., Bai, S., & Lu, X. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3378265 · Cited by 13

An ultra-specific image dataset for automated insect identification

Abeywardhana, L., DANGALLE, C. D., Nugaliyadde, A., & Mallawarachchi, Y. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11693-3 · Cited by 13

E2Net: Excitative-Expansile Learning for Weakly Supervised Object Localization

Chen, Z., Cao, L., Shen, Y., Lian, F., Wu, Y., & Ji, R. (2021) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3474085.3475211 · Cited by 13

Understanding the Effects of Pre-Training for Object Detectors via Eigenspectrum

Shinya, Y., Simo‐Serra, E., & Suzuki, T. (2019) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2019.00242 · Cited by 12

Magic-Wall: Visualizing Room Decoration by Enhanced Wall Segmentation

Liu, T., Wei, Y., Zhao, Y., Liu, S., & Wei, S. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2908064 · Cited by 12

An Accurate Real-Time License Plate Detection Method Based On Deep Learning Approaches

Khazaee, S., Tourani, A., Soroori, S., Shahbahrami, A., & Suen, C. Y. (2021) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s0218001421600089 · Cited by 11

Data enhancement and feature extraction optimization in tunnel surface defect detection: Combining DCGAN-RC and Repvit-YOLO methods

Li, S., Li, S., Li, H., & Zhou, Z. (2025) · Engineering Failure Analysis · doi:10.1016/j.engfailanal.2025.109715 · Cited by 10

Smart extensions to regular cameras in the industrial environment

Brezani, S., Hrasko, R., & Vojtáš, P. (2022) · Procedia Computer Science · doi:10.1016/j.procs.2022.01.228 · Cited by 10

Towards Proactive Surveillance through CCTV Cameras under Edge-Computing and Deep Learning

Jaleel, A., Khurshid, S. K., Mustafa, R., Aamir, K. M., Tahir, M., & Ziar, R. A. (2022) · Mathematical Problems in Engineering · doi:10.1155/2022/7001388 · Cited by 10

Self-Balanced R-CNN for instance segmentation

Rossi, L., Karimi, A., & Prati, A. (2022) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2022.103595 · Cited by 10

GPD-Nodule: A Lightweight Lung Nodule Detection and Segmentation Framework on Computed Tomography Images Using Uniform Superpixel Generation

Modak, S., Abdel‐Raheem, E., & Rueda, L. G. (2024) · IEEE Access · doi:10.1109/access.2024.3485000 · Cited by 9

Quantum machine learning for recognition of defects in ultrasonic imaging

Dubey, A., Gantala, T., Ray, A., Prabhakar, A., & Rajagopal, P. (2024) · NDT & E International · doi:10.1016/j.ndteint.2024.103262 · Cited by 9

An Application of Deep Learning Models for the Detection of Cocoa Pods at Different Ripening Stages: An Approach with Faster R-CNN and Mask R-CNN

Restrepo-Arias, J. F., Montoya-Castaño, M. J., Espriella, M. F. M.-D. L., & Branch, J. W. (2025) · Computation · doi:10.3390/computation13070159 · Cited by 10

Recursively Refined R-CNN: Instance Segmentation with Self-RoI Rebalancing

Rossi, L., Karimi, A., & Prati, A. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-89128-2_46 · Cited by 9

Anchor-Intermediate Detector: Decoupling and Coupling Bounding Boxes for Accurate Object Detection

Lv, Y., Li, M., He, Y., He, Z., Li, S., & Yang, A. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00577 · Cited by 11

Towards High-Performance Object Detection: Task-Specific Design Considering Classification and Localization Separation

Kim, J. U., Kim, S. T., Kim, E. S., Moon, S.-K., & Ro, Y. M. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054600 · Cited by 9

Fast-armored target detection based on multi-scale representation and guided anchor

Meng, F., Wang, X., Shao, F., Wang, D., & Hu, X.-D. (2019) · Defence Technology · doi:10.1016/j.dt.2019.11.009 · Cited by 9

A Novel Framework for 3D-2D Vertebra Matching

Yu, H., Fu, Y. L., Yu, H., Wei, Y., Wang, X., Jiao, J., Bramlet, M. T., Kesavadas, T., Shi, H., Wang, Z., et al. (2019) · IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR) · doi:10.1109/mipr.2019.00029 · Cited by 8

CAPN: a Combine Attention Partial Network for glove detection

Yu, F. Q., Zhu, J., Chen, Y., Liu, S., & Jiang, M. (2023) · PeerJ Computer Science · doi:10.7717/peerj-cs.1558 · Cited by 8

Refactored Maskformer: Refactor localization and classification for improved universal image segmentation

Zhu, X., Dong, X., Yu, W., Liang, H., & Kong, B. (2025) · Displays · doi:10.1016/j.displa.2025.102981 · Cited by 8

Statistical Precision-Recall Curves for Object Detection Algorithms Performance Measurement

Kuznetsova, A. A. (2021) · Studies in systems, decision and control · doi:10.1007/978-3-030-66077-2_27 · Cited by 8

Design and Usability Evaluation of an Annotated Video–Based Learning Environment for Construction Engineering Education

Olayiwola, J., Akanmu, A. A., Gao, X., Murzi, H., & Afsari, K. (2023) · Journal of Computing in Civil Engineering · doi:10.1061/jccee5.cpeng-5206 · Cited by 8

SGR: An Improved Point-Based Method for Remote Sensing Object Detection via Dual-Domain Alignment Saliency-Guided RepPoints

Mai, S., You, Y., & Feng, Y. (2024) · Remote Sensing · doi:10.3390/rs16020250 · Cited by 8

Mutual-Supervised Feature Modulation Network for Occluded Pedestrian Detection

He, Y., Zhu, C., & Yin, X.-C. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412981 · Cited by 8

Prototype-based cross-modal object tracking

Liu, L., Li, C., Wang, F., Shen, L., & Tang, J. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.102941 · Cited by 7

Cotton pest and disease diagnosis via YOLOv11-based deep learning and knowledge graphs: a real-time voice-enabled edge solution

Zhong, M., Wei, L., & Mo, H. (2025) · Frontiers in Plant Science · doi:10.3389/fpls.2025.1671755 · Cited by 7

Vision Fourier transformer empowered multi-modal imaging system for ethane leakage detection

Bin, J., Rogers, S., & Liu, Z. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102266 · Cited by 7

OV-DAR: Open-Vocabulary Object Detection and Attributes Recognition

Chen, K., Jiang, X., Wang, H., Yan, C., Gao, Y. F., Tang, X., Hu, Y. G., & Xie, W. (2024) · International Journal of Computer Vision · doi:10.1007/s11263-024-02144-1 · Cited by 7

HLDNet: Abandoned Object Detection Using Hand Luggage Detection Network

Kim, D., Kim, H., Mok, Y., & Paik, J. (2021) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2021.3099288 · Cited by 7

B-PesNet: Smoothly Propagating Semantics for Robust and Reliable Multi-Scale Object Detection for Secure Systems

Rao, Y., Mu, H., Yang, Z., Zheng, W., Wang, F., Pu, J., & Zeng, S. (2022) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2022.020331 · Cited by 6

Adaptive Multi-task Learning for Few-Shot Object Detection

Ren, Y., Li, Y., & Kong, A. W. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72667-5_17 · Cited by 7

A Framework of Maximum Feature Exploration Oriented Remote Sensing Object Detection

Li, Y., Xing, Y., Wang, Z., Xiao, T., Song, Q., Li, W., & Wang, J. (2022) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2022.3228689 · Cited by 6

Real-time Target Recognition for Urban Autonomous Vehicles Based on Information Fusion

Peilin, X., Wu, Y., Yin, G., Shuaipeng, L., Yiheng, L., Wenhan, H., & Zhang, Y. (2020) · Journal of Mechanical Engineering · doi:10.3901/jme.2020.12.165 · Cited by 6

TSNet : Tree structure network for human pose estimation

Wan, T., Luo, Y., Zhang, Z., & Ou, Z. (2021) · Signal Image and Video Processing · doi:10.1007/s11760-021-01999-y · Cited by 6

Forestry Pests Identification and Classification Based on Improved YOLO v5s

Zhang, L., Yin, L., Liu, L., Zhuo, R., & Zhuo, Y. (2021) · International Conference on Electronic Information Engineering and Computer Science (EIECS) · doi:10.1109/eiecs53707.2021.9588027 · Cited by 6

Shape Prior is Not All You Need: Discovering Balance Between Texture and Shape Bias in CNN

Chung, H., & Park, K. H. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26284-5_30 · Cited by 7

EMC-YOLO: a feature enhancement and fusion based surface defect detection for hot rolled strip steel

Zhu, X., Wan, X., & Zhang, M. (2025) · Engineering Research Express · doi:10.1088/2631-8695/ada7c4 · Cited by 5

Improving Industrial Safety Gear Detection through Re-ID conditioned Detector

Ravikiran, M., & Sen, S. (2019) · IEEE Applied Imagery Pattern Recognition Workshop · doi:10.1109/aipr47015.2019.9174597 · Cited by 5

An Efficient Approach Using Knowledge Distillation Methods to Stabilize Performance in a Lightweight Top-Down Posture Estimation Network

Park, C., Lee, H. S., Kim, W. J., Bae, H. B., Lee, J., & Lee, S. (2021) · Sensors · doi:10.3390/s21227640 · Cited by 5

Efficacy of Annotated Video-Based Learning Environment for Drawing Students’ Attention to Construction Practice Concepts

Olayiwola, J., Yusuf, A. O., Akanmu, A. A., Gonsalves, N. J., & Abraham, Y. S. (2023) · Journal of Construction Engineering and Management · doi:10.1061/jcemd4.coeng-13778 · Cited by 5

Improved YOLOv5s-Based Traffic Signal Detection Algorithm

黄, 寅. (2023) · Modeling and Simulation · doi:10.12677/mos.2023.126532 · Cited by 5

Accelerated and Energy-Efficient Galaxy Detection: Integrating Deep Learning with Tensor Methods for Astronomical Imaging

Farías, H., Solar, M., Jaque, M., & Damke, G. (2025) · Universe · doi:10.3390/universe11020073 · Cited by 5

HKE-GCN: Heatmaps-guided Keypoints Encoder and Graph Convolutional Network for Human Pose Estimation

Xia, H., Wang, Y., Wang, X., Xiong, S., & Yu, Z. (2022) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn55064.2022.9892251 · Cited by 5

Towards Precise Weakly Supervised Object Detection via Interactive Contrastive Learning of Context Information

Lai, Q., Vong, C., Shi, S.-Q., & Chen, C. L. P. (2024) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2024.3436853 · Cited by 5

Enhanced Detection Reliability for Human Tracking Based Video Analytics

Fu, Z., Lai, X. Q., & Naqvi, S. M. (2019) · International Conference on Information Fusion (FUSION) · doi:10.23919/fusion43075.2019.9011428 · Cited by 5

An ultra-specific image dataset for automated insect identification

Abeywardhana, L., DANGALLE, C. D., Nugaliyadde, A., & Mallawarachchi, Y. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11450-6 · Cited by 5

Research on YOLOv8 Object Detection Algorithm in UAV ScenariosPreprint

Li, S., Chen, F., Sun, Z., Zhu, Z., Zhou, L., & Tang, K. (2024) · Research Square · doi:10.21203/rs.3.rs-3995816/v1 · Cited by 5

Few-Shot Object Detection on Remote Sensing Images Based on Decoupled Training, Contrastive Learning, and Self-Training

Zhang, S., Zhang, X., Xu, Y., & Wang, K. (2026) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2025.3650394 · Cited by 4

An underwater target recognition algorithm incorporating improved attention mechanism and downsampling

Zhu, Q., Cen, Q., Wang, Y., Chen, W., & Liu, S. (2024) · The Visual Computer · doi:10.1007/s00371-024-03437-9 · Cited by 4

Faster R-CNN-MobileNetV3 Based Micro Expression Detection for Autism Spectrum Disorder

Li, H., Gu, Y., Han, J., Sun, Y., Lei, H., Li, C., & Xu, N. (2025) · AI medicine. · doi:10.53941/aim.2025.100002 · Cited by 4

Enhanced YOLO architecture for real-time coal gangue detection with lightweight design

Wen, L., Hong, Y., Pan, R., Su, J., Wang, L., & Bao, S. (2025) · Signal Image and Video Processing · doi:10.1007/s11760-025-04787-0 · Cited by 4

Understanding human responses to errors in a collaborative human-robot selective harvesting task

Huang, Z., Salazar-Gomez, A., Bird, R., Kalsi, A. S., Jansen, C., Liu, Z., Miyauchi, G., Parsons, S., & Sklar, E. I. (2020) · Journal of robotics & autonomous systems · doi:10.31256/xp9yb4h · Cited by 4

Driver Cell-phone Use Detection Based on CornerNet-Lite Network

He, A., Chen, G., Zheng, W., Ni, Z., Zhang, Q., & Zhu, Z. (2021) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/632/4/042004 · Cited by 4

Deep Learning Techniques for Explosive Weapons and Arms Detection: A Comprehensive Review

Bhatt, A., & Ganatra, A. P. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-5974-7_46 · Cited by 4

Deteksi Bola dan Gawang dengan Metode YOLO Menggunakan Kamera Omnidirectional pada Robot KRSBI-B

Sanubari, F. F., & Puriyanto, R. D. (2022) · Buletin Ilmiah Sarjana Teknik Elektro · doi:10.12928/biste.v4i2.6712 · Cited by 7

Image Filtering Techniques for Object Recognition in Autonomous Vehicles

Hien, N. L. H., Kor, A.-L., Ang, M. C., Rondeau, É., & Georges, J. (2024) · JUCS - Journal of Universal Computer Science · doi:10.3897/jucs.102428 · Cited by 4

An Experiment on Human-Robot Interaction in a Simulated Agricultural Task

Huang, Z., Miyauchi, G., Salazar-Gomez, A., Bird, R., Kalsi, A. S., Jansen, C., Liu, Z., Parsons, S., & Sklar, E. I. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-63486-5_25 · Cited by 4

Drawing and Analysis of Bounding Boxes for Object Detection with Anchor-Based Models

Madan, M., Reich, C., & Hassenpflug, F. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-31435-3_24 · Cited by 4

Dually Supervised Feature Pyramid for Object Detection and SegmentationPreprint

Yang, F., Lu, C., Guo, Y., Latecki, L. J., & Ling, H. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1912.03730 · Cited by 4

Employing cross-domain modelings for robust object detection in dynamic environment of autonomous vehicles

Rawlley, O., Gupta, S. R., Kathera, H., Katyal, S., & Batwara, Y. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-19409-z · Cited by 3

Improved Cassava Plant Disease Classification with Leaf Detection

Chai, M. X., Fam, Y. D., Octaviano, Q. N., Pee, C.-Y., Wong, L.-K., Tan, M. I. S. M. H., & See, J. (2024) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipaasc63619.2025.10849031 · Cited by 4

YOLOv11n-UAV: improved YOLOv11n model for detecting small UAVs using infrared images on complex backgrounds

Nguyen, P. T., & Nguyen, L. H. (2025) · Neural Computing and Applications · doi:10.1007/s00521-025-11305-3 · Cited by 3

YOLOv8n-DSDL: A lightweight dual-backbone network with decoupled self-attention for cotton maturity detection

Zhong, M., Wei, L., & Mo, H. (2025) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-025-00081-8 · Cited by 3

E2VTS: Energy-Efficient Video Text Spotting from Unmanned Aerial Vehicles

Hu, Z., Pi, P., Wu, Z., Xue, Y., Shen, J., Tan, J., Lian, X., Wang, Z., & Liu, J. Y. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00101 · Cited by 3

Online Feature Classification and Clustering for Transformer-based Visual Tracker

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A lightweight defect detection algorithm for escalator steps

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