InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

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

Attention Is All You Need

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404

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

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333

Going deeper with convolutions

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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et al. (2020) · arXiv · doi:10.48550/arxiv.2010.11929 · Cited by 47,472

Microsoft COCO: Common Objects in Context

Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., & Guo, B. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00986 · Cited by 35,534

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

Solar photovoltaic module defect detection based on deep learning

ZHANG, Y., Zhang, X., & Tu, D. (2024) · Measurement Science and Technology · doi:10.1088/1361-6501/ad7d28 · Cited by 16

Fanet: Feature Amplification Network for Semantic Segmentation in Cluttered Background

Ali, M. R., Javaid, M., Noman, M., Fiaz, M., & Khan, S. S. (2024) · Proceedings - International Conference on Image Processing · doi:10.1109/icip51287.2024.10647349 · Cited by 17

Vision-based sorting in mixed food-inorganic waste stream

Chen, F., Ye, L., Zheng, Z. P., Zhao, Y., Zhou, T., & Huang, Q. (2024) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2024.107964 · Cited by 16

Exploring Context Alignment and Structure Perception for Building Change Detection

Wang, Q., Zhang, M., Ren, J., & Li, Q. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3540013 · Cited by 16

U-DECN: End-to-End Underwater Object Detection ConvNet With Improved Denoising Training

Liu, Z., Wang, B., Wang, B., & Li, Y. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3595158 · Cited by 16

HSENet: Hierarchical semantic-enriched network for multi-modal image fusion

Liu, X., Ming, R., Ду, С., He, L., Luo, H., & Xiao, G. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.112043 · Cited by 15

RSD-YOLO: An improved YOLOv7-tiny framework for oat disease severity identification with integration of ReXNet and decoupled head

Zhang, Y., Xu, Y., Xu, T., Wang, C., Li, C., & Wang, H. (2025) · Smart Agricultural Technology · doi:10.1016/j.atech.2025.101433 · Cited by 15

Semantic Segmentation of Crops and Weeds with Probabilistic Modeling and Uncertainty Quantification

Celikkan, E., Saberioon, M., Herold, M., & Klein, N. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00065 · Cited by 15

DreamTeacher: Pretraining Image Backbones with Deep Generative Models

Li, D., Ling, H., Kar, A., Acuna, D., Kim, S. W., Kreis, K., Torralba, A. B., & Fidler, S. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01531 · Cited by 19

Semantic-Preserving Image Coding Based on Conditional Diffusion Models

Pezone, F., Musa, O., Caire, G., & Barbarossa, S. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10447279 · Cited by 18

HDA-pose: a real-time 2D human pose estimation method based on modified YOLOv8

Dong, C., Tang, Y., & Zhang, L. (2024) · Signal Image and Video Processing · doi:10.1007/s11760-024-03274-2 · Cited by 15

A lightweight Yunnan Xiaomila detection and pose estimation based on improved YOLOv8

Wang, F., Tang, Y., Gong, Z., Jiang, J., Chen, Y., Xu, Q., Hu, P., & Zhu, H. (2024) · Frontiers in Plant Science · doi:10.3389/fpls.2024.1421381 · Cited by 15

Instance-Aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation

Lei, X., Wang, M., Zhou, W., Li, L., & Li, H. (2024) · 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/cvpr52733.2024.01545 · Cited by 21

Region-Based Representations Revisited

Shlapentokh-Rothman, M., Blume, A., Xiao, Y., Wu, Y., Sethuraman, T. V., Tao, H., Lee, J., Torres, W., Wang, Y.-X., & Hoiem, D. (2024) · 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/cvpr52733.2024.01619 · Cited by 19

Enhancing Tampered Text Detection Through Frequency Feature Fusion and Decomposition

Chen, Z., Shen, C., Yao, T., Sun, K., Ding, S., Lin, X., Cao, L., & Ji, R. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73414-4_12 · Cited by 16

LCIRE-Net: Lightweight Cross-Modal Information Interaction for Road Feature Extraction From Remote Sensing Images and GPS Trajectory/LiDAR

Duan, Y., Yang, D., Qu, X., Zhang, L., Lü, C., Gan, P., Yuan, S., Qin, H., & Qu, J. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3516840 · Cited by 15

UV-Mamba: A DCN-Enhanced State Space Model for Urban Village Boundary Identification in High-Resolution Remote Sensing Images

Li, L., Chen, B. M., Zou, X., Xing, J., & Tao, P. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10888896 · Cited by 17

A Deep Learning-Based Time-Frequency Scheme for Ship Detection Using HFSWR

Huang, D., Zhou, H., Tian, Y., Yang, Z., & Huang, W. (2024) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3518781 · Cited by 14

RadOcc: Learning Cross-Modality Occupancy Knowledge through Rendering Assisted Distillation

Zhang, H., Yan, X., Bai, D., Gao, J., Wang, P., Liu, B., Cui, S. R., & Li, Z. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i7.28533 · Cited by 14

Heavy and Lightweight Deep Learning Models for Semantic Segmentation: A Survey

Cărunta, C., Cărunta, A., & Popa, C.-A. (2025) · IEEE Access · doi:10.1109/access.2025.3529812 · Cited by 17

AppleYOLO: Apple yield estimation method using improved YOLOv8 based on Deep OC-SORT

Tan, S., Kuang, Z., & Jin, B. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.126764 · Cited by 14

Mind the Map! Accounting for Existing Maps When Estimating Online HDMaps from Sensors

Sun, R., Li, Y., Lingrand, D., & Precioso, F. (2025) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61041.2025.00170 · Cited by 14

Real-time semantic segmentation in traffic scene using Cross Stage Partial-based encoder–decoder network

Zhou, L., Chen, G., Liu, L., Wang, R., & Knoll, A. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.106901 · Cited by 14

DP-YOLO: Effective Improvement Based on YOLO Detector

Wang, C., Wang, Q., Qian, Y., Hu, Y., Xue, Y. W., & Wang, H. (2023) · Applied Sciences · doi:10.3390/app132111676 · Cited by 14

A lightweight and scalable greenhouse mapping method based on remote sensing imagery

Chen, W., Wang, Q., Wang, D., Xu, Y., He, Y., Yang, L., & Tang, H. (2023) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2023.103553 · Cited by 14

The Target Detection of Wear Particles in Ferrographic Images Based on the Improved YOLOv8

Wong, J., Wei, H., Zhou, D., & Cao, Z. (2024) · Lubricants · doi:10.3390/lubricants12080280 · Cited by 13

FishFocusNet: An improved method based on YOLOv8 for underwater tropical fish identification

Lu, Z., Zhu, X., Guo, H., Xie, X., Chen, X., & Quan, X. (2024) · IET Image Processing · doi:10.1049/ipr2.13202 · Cited by 13

Image CAPTCHAs: When Deep Learning Breaks the Mold

Moradi, M., Moradi, M., Palazzo, S., Rundo, F., & Spampinato, C. (2024) · IEEE Access · doi:10.1109/access.2024.3442976 · Cited by 13

GlobalSR: Global context network for single image super-resolution via deformable convolution attention and fast Fourier convolution

Chen, Q., Wen, W., & Qin, J. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106686 · Cited by 13

Open-World Semantic Segmentation Including Class Similarity

Sodano, M., Magistri, F., Nunes, L., Behley, J., & Stachniss, C. (2024) · 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/cvpr52733.2024.00307 · Cited by 13

Joint Image Restoration For Domain Adaptive Object Detection In Foggy Weather Condition

Ma, J., Meng, L., Zhou, G., & Jia, Z. (2024) · Proceedings - International Conference on Image Processing · doi:10.1109/icip51287.2024.10647560 · Cited by 13

DSFNet: Video Salient Object Detection Using a Novel Lightweight Deformable Separable Fusion Network

Singh, H., Verma, M., & Cheruku, R. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3470045 · Cited by 13

YOLOv8-WTDD: multi-scale defect detection algorithm for wind turbines

Yu, X., Peng, Y., Zheng, S., Du, Q., & Wang, D. (2024) · The Journal of Supercomputing · doi:10.1007/s11227-024-06487-x · Cited by 13

Hierarchical Scale Awareness for object detection in Unmanned Aerial Vehicle Scenes

Wang, S., Wan, C., Yan, J., Li, S., Sun, T., Chi, J., Yang, G., Chen, C., & Yu, T. (2024) · Applied Soft Computing · doi:10.1016/j.asoc.2024.112487 · Cited by 14

ADMNet: adaptive deformable convolution large model combining multi-level progressive fusion for Building Change Detection

Mei, L., Yu, H., Ye, Z., Xu, C., Lei, C., & Yang, W. (2025) · Geo-spatial Information Science · doi:10.1080/10095020.2024.2448232 · Cited by 13

A Small-Sample Target Detection Method of Side-Scan Sonar Based on CycleGAN and Improved YOLOv8

Zheng, Y., Yan, J., Meng, J., & Liang, M. (2025) · Applied Sciences · doi:10.3390/app15052396 · Cited by 13

Adaptive learning network for detecting pavement distresses in complex environments

Wang, D. W., Zhang, A. A., Peng, Y. L., Wei, Y.-J., Cheng, H., & Shang, J. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110784 · Cited by 13

A lightweight and robust detection network for diverse glass surface defects via scale- and shape-aware feature extraction

Yu, H. J., Wang, J., Yang, J., Liang, Y., Li, Z., Wang, Z., He, H., Zhang, X., & Lu, G. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110640 · Cited by 13

PonderV2: Improved 3D Representation With a Universal Pre-Training Paradigm

Zhu, H., Yang, H., Wu, X., Huang, D., Zhang, S., He, X., Zhao, H., Shen, C., Qiao, Y., He, T., et al. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3561598 · Cited by 47

Beyond Human Detection: A Benchmark for Detecting Common Human Posture

Li, Y., Wu, Y., Chen, X., Chen, H., Kong, D., Tang, H., & Li, S. (2023) · Sensors · doi:10.3390/s23198061 · Cited by 12

CAMEL: Co-Designing AI Models and eDRAMs for Efficient On-Device Learning

Zhang, S. Q., Tambe, T., Cuevas, N., Wei, G.-Y., & Brooks, D. M. (2024) · IEEE International Symposium on High-Performance Computer Architecture (HPCA) · doi:10.1109/hpca57654.2024.00071 · Cited by 16

FEFA: Frequency Enhanced Multi-Modal MRI Reconstruction With Deep Feature Alignment

Chen, X., Ma, L., Ying, S., Shen, D. G., & Zeng, T. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3432139 · Cited by 12

Deformable attention mechanism-based YOLOv7 structure for lung nodule detection

Liu, Y., & Ao, Y. (2024) · The Journal of Supercomputing · doi:10.1007/s11227-024-06381-6 · Cited by 12

Swimming-YOLO: a drowning detection method in multi-swimming scenarios based on improved YOLO algorithm

Jiang, X., Tang, D., Xu, W., Zhang, Y., & Ye, L. (2024) · Signal Image and Video Processing · doi:10.1007/s11760-024-03744-7 · Cited by 12

MLSA-YOLO: a multi-level feature fusion and scale-adaptive framework for small object detection

Peng, J., Lv, K., Wang, G., Xiao, W., Ran, T., & Yuan, L. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-06961-0 · Cited by 13

A High-Performance and Lightweight Maritime Target Detection Algorithm

Sun, S., Xu, Z., Cao, X., Zheng, J., Yang, J., & Jin, N. (2025) · Remote Sensing · doi:10.3390/rs17061012 · Cited by 12

Enhanced lightweight detection of small and tiny objects in high-resolution images using object tracking-based region of interest proposal

Kos, A., Majek, K., & Belter, D. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110852 · Cited by 14

Dual-Modal Prior Semantic Guided Infrared and Visible Image Fusion for Intelligent Transportation System

Li, J., Bai, L., Yang, B., Li, C., Ma, L., Cui, L., & Hancock, E. R. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3562267 · Cited by 12

A lightweight deep learning framework for wild berry detection in complex natural environments

Zhang, X., Li, F., Hu, X., & Fang, J. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110918 · Cited by 12

Identification of Low‐Value Defects in Infrared Images of Porcelain Insulators Based on STCE‐YOLO Algorithm

Pei, S., Wang, W., Hu, C., Li, K., Sun, H., Wu, M., & Lan, B. (2025) · Energy Science & Engineering · doi:10.1002/ese3.70136 · Cited by 12

YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes

Zeng, Y., Wang, X., Zou, J., & Wu, H. (2025) · Remote Sensing · doi:10.3390/rs17111948 · Cited by 12

HDRoad: An encoder-decoder architecture with hybrid attention and directional prior for efficient road extraction from remote sensing images

He, F., Liu, S., Liu, S., Jin, Y., Xie, H. X., & Tong, X. (2025) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2025.06.014 · Cited by 13

Higher greenery visibility is not necessarily better: A quantitative approach to evaluating window view quality in residential buildings

Wang, Y., Wang, D., & Zhang, X. (2025) · Building and Environment · doi:10.1016/j.buildenv.2025.113563 · Cited by 12

Automatic Defect Detection in Sewer Network Using Deep Learning Based Object Detector

Ha, D. B., Schalter, B., White, L., & Köhler, J. (2023) · International Conference on Image Processing and Vision Engineering (IMPROVE) · doi:10.5220/0011986300003497 · Cited by 12

Local and Global Contextual Features Fusion for Pedestrian Intention Prediction

Azarmi, M., Rezaei, M., Hussain, T., & Qian, C. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-43763-2_1 · Cited by 12

An Improved Deeplabv3+ Model for Semantic Segmentation of Urban Environments Targeting Autonomous Driving

Wang, W., He, H., & Ma, C. (2023) · International Journal of Computers Communications & Control · doi:10.15837/ijccc.2023.6.5879 · Cited by 12

Flood Detection in Polarimetric SAR Data Using Deformable Convolutional Vision Model

Yu, H., Wang, R., Li, P., & Zhang, P. (2023) · Water · doi:10.3390/w15244202 · Cited by 12

An Effective and Lightweight Full-Scale Target Detection Network for UAV Images Based on Deformable Convolutions and Multi-Scale Contextual Feature Optimization

Yu, W., Zhang, J., Liu, D., Xi, Y., & Wu, Y. (2024) · Remote Sensing · doi:10.3390/rs16162944 · Cited by 11

Multispectral Semantic Segmentation for UAVs: A Benchmark Dataset and Baseline

Li, Q. S., Yuan, H., Fu, T., Yu, Z., Zheng, B., & Chen, S. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3457674 · Cited by 12

Strong but Simple: A Baseline for Domain Generalized Dense Perception by CLIP-Based Transfer Learning

Hümmer, C., Schwonberg, M., Zhou, L., Cao, H., Knoll, A., & Gottschalk, H. (2024) · Lecture notes in computer science · doi:10.1007/978-981-96-0972-7_27 · Cited by 13

DHVT: Dynamic Hybrid Vision Transformer for Small Dataset Recognition

Lu, Z., Liu, C., Chang, X., Zhang, Y., & Xie, H. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3528228 · Cited by 13

A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario

Zedda, L., Loddo, A., & Ruberto, C. D. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.109704 · Cited by 13

SPAFPN: Wear a multi-scale feature fusion scarf around neck for real-time object detector

Bian, Z., Yao, B., & Li, Q. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103034 · Cited by 11

An Overview of AI-Guided Thyroid Ultrasound Image Segmentation and Classification for Nodule Assessment

Savelonas, M. A. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9100255 · Cited by 13

Radarnext: lightweight and real-time 3D object detector based on 4D mmWave imaging radar

Jia, L., Guan, R., Zhao, H., Zhao, Q., Man, K. L., Smith, J., Liu, Y., & Yue, Y. (2025) · EURASIP Journal on Advances in Signal Processing · doi:10.1186/s13634-025-01271-2 · Cited by 11

An Advanced Software Platform and Algorithmic Framework for Mobile DBH Data Acquisition

Zhang, J., Liang, H., Tong, S., Zhou, Y., & Kan, J. (2023) · Forests · doi:10.3390/f14122334 · Cited by 11

Optimal Configuration of Multi-Task Learning for Autonomous Driving

Jun, W., Son, M., Yoo, J., & Lee, S. (2023) · Sensors · doi:10.3390/s23249729 · Cited by 11

UGNet: Uncertainty aware geometry enhanced networks for stereo matching

Qi, Z., Zhang, J., Fang, F., Wang, T., & Zhang, G. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110410 · Cited by 11

On the Importance of Large Objects in CNN Based Object Detection Algorithms

Saad, A. B., Facciolo, G., & Davy, A. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00059 · Cited by 11

DDC-PIM: Efficient Algorithm/Architecture Co-Design for Doubling Data Capacity of SRAM-Based Processing-in-Memory

Duan, C., Yang, J., He, X., Qi, Y., Wang, Y., Wang, Y., He, Z., Yan, B., Wang, X., Jia, X., et al. (2023) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2023.3330819 · Cited by 10

Epurate-Net: Efficient Progressive Uncertainty Refinement Analysis for Traffic Environment Urban Road Detection

Han, T., Chen, S., Li, C., Wang, Z., Su, J., Huang, M., & Cai, G. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3345901 · Cited by 10

TransFed: A way to epitomize Focal Modulation using Transformer-based Federated Learning

Ashraf, T., Mir, F. B. A., & Gillani, I. A. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00061 · Cited by 10

Classification of Astronomical Spectra Based on Multiscale Partial Convolution

Wu, J., He, Y., Wang, W., Qu, M., Jiang, B., & Zhang, Y. (2024) · The Astronomical Journal · doi:10.3847/1538-3881/ad38ae · Cited by 10

DART: An automated end-to-end object detection pipeline with data Diversification, open-vocabulary bounding box Annotation, pseudo-label Review, and model Training

Xin, C., Hartel, A., & Kasneci, E. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125124 · Cited by 11

RoScenes: A Large-Scale Multi-view 3D Dataset for Roadside Perception

Zhu, X., Sheng, H., Cai, S., Deng, B., Yang, S., Liang, Q., Chen, K., Gao, L., Song, J., & Ye, J. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72940-9_19 · Cited by 12

HawkEye Conv-Driven YOLOv10 with Advanced Feature Pyramid Networks for Small Object Detection in UAV Imagery

Li, Y., Yang, W., Wang, L., Tao, X., Yin, Y., & Chen, D. (2024) · Drones · doi:10.3390/drones8120713 · Cited by 10

Efficient and accurate tobacco leaf maturity detection: an improved YOLOv10 model with DCNv3 and efficient local attention integration

Shi, Y., Wang, H., Wang, F., Wang, Y., Liu, J., Zhao, L., Wang, H., Zhang, F., Cheng, Q., & Qing, S. (2025) · Frontiers in Plant Science · doi:10.3389/fpls.2024.1474207 · Cited by 10

BGLE-YOLO: A Lightweight Model for Underwater Bio-Detection

Zhao, H., Xu, C., Chen, J., Zhang, Z., & Wang, X. (2025) · Sensors · doi:10.3390/s25051595 · Cited by 10

3 rd Workshop on Maritime Computer Vision (MaCVi) 2025: Challenge Results

Kiefer, B., Žust, L., Muhovič, J., Kristan, M., Perš, J., Teršek, M., Mudenagudi, U., Desai, C., Wiliem, A., Kreis, M., et al. (2025) · IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) · doi:10.1109/wacvw65960.2025.00170 · Cited by 11

Nondestructive freshness recognition of chicken breast meat based on deep learning

Jian, R., Li, G., Xie, J., & Shi, G. (2025) · Scientific Reports · doi:10.1038/s41598-025-13576-1 · Cited by 10

UniAlign: Scaling Multimodal Alignment within One Unified Model

Zhou, B., Li, L., Wang, Y., Liu, H., Yao, Y., & Wang, W. (2025) · 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/cvpr52734.2025.02760 · Cited by 13

A Lightweight Spatial–Spectral Deformable CNN for UAV Hyperspectral Image Classification

Ma, X., Zhang, M., Kan, Z., Gao, Y., & Li, W. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3608510 · Cited by 10

Multi-module enhanced low-light object detection: From image enhancement to adaptive feature fusion

Ci, W., Hou, H., Lu, S., Deng, H., & Ma, J.-H. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.104097 · Cited by 10

LDA-DETR: A lightweight dynamic attention-enhanced DETR for small object detection

Shi, Y., Li, J., Jia, Y., & Hong, Q. (2026) · PLoS ONE · doi:10.1371/journal.pone.0340977 · Cited by 10

Improved YOLOv5 for Aerial Images Based on Attention Mechanism

Li, Z., Fan, B., Xu, Y., & Sun, R. (2023) · IEEE Access · doi:10.1109/access.2023.3277931 · Cited by 10

Simplified Routing Mechanism for Capsule Networks

Hollósi, J., Ballagi, Á., & Pozna, C. R. (2023) · Algorithms · doi:10.3390/a16070336 · Cited by 10

DVST: Deformable Voxel Set Transformer for 3D Object Detection from Point Clouds

Ning, Y., Cao, J., Bao, C., & Hao, Q. (2023) · Remote Sensing · doi:10.3390/rs15235612 · Cited by 10

SDMSEAF-YOLOv8: a framework to significantly improve the detection performance of unmanned aerial vehicle images

Li, L., Liu, X., Chen, X., Yin, F., Chen, B., Wang, Y., & Meng, F. (2024) · Geocarto International · doi:10.1080/10106049.2024.2339294 · Cited by 10

CARD: Semantic Segmentation With Efficient Class-Aware Regularized Decoder

Huang, Y., Kang, D., Chen, L., Jia, W., He, X., Duan, L., Zhe, X., & Bao, L. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3395132 · Cited by 10

PIRN: Phase Invariant Reconstruction Network for infrared image super-resolution

Dan, J., Jin, T., Chi, H., Liu, M., Yu, J., Cao, K., Xinjing, Y., Luo, Z., & Xie, H. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128221 · Cited by 10

CAM Back Again: Large Kernel CNNs from a Weakly Supervised Object Localization Perspective

Yasuki, S., & Taki, M. (2024) · 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/cvpr52733.2024.00040 · Cited by 12

Rethinking and Improving Visual Prompt Selection for In-Context Learning Segmentation

Suo, W., Lai, L., Sun, M., Zhang, H., Wang, P., & Zhang, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72952-2_2 · Cited by 13

Merging Context Clustering with Visual State Space Models for Medical Image SegmentationPreprint

Zhu, Y., Zhang, D., Lin, Y., Feng, Y., & Tang, J. (2025) · Qeios · doi:10.32388/nuppza · Cited by 10

An efficient multi-order cascade distillation model for the detection of small targets and occluded objects in transmission line inspection

Qu, Z., Zang, J., Dong, Y., Qu, N., Song, S., Jiang, T., Li, M., Liang, F., & Li, L. (2023) · Measurement · doi:10.1016/j.measurement.2023.114000 · Cited by 9

Enabling Foundation Models: A Distributed Collaboration Framework Based on Graph Federated Learning

Chen, J., Guo, S., Qi, Q., Hao, J., Guo, S., & Qiu, X. (2024) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2024.3436695 · Cited by 9

A generative adversarial network for multiple reads reconstruction in DNA storage

Zheng, X., Xie, R., Yao, X., Su, Y., Chu, L., Xu, P., & Liu, W. (2024) · Scientific Reports · doi:10.1038/s41598-024-83806-5 · Cited by 9

YOLO-ITC: A New YOLO Method for Instance Segmentation of Individual Tree Crowns

Sun, Z., Xue, B., Zhang, M., & Schindler, J. (2025) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2025.3543833 · Cited by 9

Ethics of Foundation Models in Computational Pathology: Overview of Contemporary Issues and Future Implications

Du, R. F., Carbonell, E. L., Huang, J., Liu, S., Wang, X., Shen, D. G., & Ke, J. (2025) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2025.3551913 · Cited by 10

Flexi-YOLO: A lightweight method for road crack detection in complex environments

Yang, J., Tian, R., Zhou, Z., Tan, X., & He, P. (2025) · PLoS ONE · doi:10.1371/journal.pone.0325993 · Cited by 9

Depth Matters: Exploring Deep Interactions of RGB-D for Semantic Segmentation in Traffic Scenes

Chen, S., Han, T., Zhang, C., Liu, W., Su, J., Wang, Z., & Cai, G. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11246921 · Cited by 10

Vision Transformers in Image Recognition

Müller, A., Hansen, L., & Ivanov, L. (2023) · Bio-QI Journal · doi:10.5281/zenodo.19614668

CvT: Introducing Convolutions to Vision Transformers

Wu, H., Xiao, B., Codella, N., Liu, M., Dai, X., Yuan, L., & Zhang, L. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00009 · Cited by 2,795

Efficient Segmentation Using Attention-Fusion Modules With Dense Predictions

Erişen, S. (2025) · IEEE Access · doi:10.1109/access.2025.3581986 · Cited by 3

An Image Equals 16x16 Words: Scaling Image Recogni:on with TransformersPreprint

Beyer, A., & Alexy, L. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5180447 · Cited by 15

ParCNetV2: Oversized Kernel with Enhanced Attention *

Xu, R., Zhang, H., Hu, W., Zhang, S. S., & Wang, X. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00529 · Cited by 8