Scholar4AI Updated 2026-11-03 14:43 UTC+09:00

ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation: papers linking to it

Zenodo · Software · 2022 · archives github.com/ultralytics/yolov5 · doi.org/10.5281/zenodo.3908559

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation (https://doi.org/10.5281/zenodo.3908559), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

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Key findings#

  • 31 papers in the tracked journals link to the Zenodo dataset ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation in their Crossref records, the first in 2022; most of them (19) in 2025.
  • By category: AI (30) and Operations Research (1); the journals with the most are Expert Systems with Applications (10), Applied Intelligence (5) and Neural Networks (3).
  • It is a Zenodo archive of ultralytics/yolov5, which other papers here link to as well.

By year#

2022: 1 paper2023: 2 papers2024: 2 papers2025: 19 papers2026: 7 papers
20222026
Papers linking to ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation by publication year
YearPapers
20221
20232
20242
202519
20267

Journals#

Journals whose papers link to ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation most
JournalPapers
Expert Systems with Applications10
Applied Intelligence5
Neural Networks3
International Journal of Computer Vision3
Knowledge-Based Systems2
Linked repositories ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation derives from or that derive from it
RepositoryRelationPapers
ultralytics/yolov5ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation is its Zenodo archive110
Papers linking to ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation, most cited first
PublishedTitleJournalAuthorsCitationsLink
2023-11-07DO-SLAM: research and application of semantic SLAM system towards dynamic environments based on object detectionApplied IntelligenceYaoguang Wei, Bingqian Zhou, Yunhong Duan et al.36cites it
2025-07-03YOLO-MSD: a robust industrial surface defect detection model via multi-scale feature fusionApplied IntelligenceYifei Ge, Zhuo Li, Lin Meng19cites it
2024-11-07PFEI-Net: A profound feature exploration and interaction network for ceramic substrate surface defect detectionExpert Systems with ApplicationsY G He, Chunming Cai, Gui Chen et al.13cites it
2022-09-19CDFF: a fast and highly accurate method for recognizing traffic signsNeural Computing and ApplicationsLanmei Wang, Wang Lizhe, Lizhe Wang et al.12cites it
2025-03-29Adaptive shape imitation and selective semantic guidance for industrial surface defect detectionExpert Systems with ApplicationsXiao Liang, Y Y Li, Xuewei Wang et al.9cites it
2023-12-15Bi-AFN++CA: Bi-directional adaptive fusion network combining context augmentation for small object detectionApplied IntelligenceHongying Zhang, Enyao Chen7cites it
2025-04-01A Multi-scale Feature Fusion Network Focusing on Small Objects in UAV-ViewCognitive ComputationJiantao Li, Cui Yu, Wenhui Wei et al.7cites it
2025-06-02A lightweight detector for small targets using forward-looking sonar in underwater search scenariosExpert Systems with ApplicationsJie Li, Wenpei Jiao, Jianlei Zhang et al.7cites it
2025-12-12A real-time surface defect detection model based on adaptive feature information selection and fusionInformation FusionLi‐Juan Liu, Shao-Qi Sun, Hamid Reza Karimi7cites it
2024-11-13Learning to Detect Novel Species with SAM in the WildInternational Journal of Computer VisionGarvita Allabadi, Ana Lucic, Yu-Xiong Wang et al.6cites it
2025-07-05Dual-level aggregation network for video-based visible-infrared group re-identificationPattern RecognitionJianghao Xiong, Xiaohua Xie, Jianhuang Lai6cites it
2025-12-21Advancing traffic object detection in complex environments: a deep learning object detection approach with vehicle-mounted UAV data for traffic scene perceptionKnowledge and Information SystemsYang Liu, Hongyu Sun, Weiqin Li et al.5cites it
2025-05-24Local Concept Embeddings for Analysis of Concept Distributions in Vision DNN Feature SpacesInternational Journal of Computer VisionGeorgii Mikriukov, Gesina Schwalbe, Korinna Bade4cites it
2025-10-04CEVG-RTNet: A real-time architecture for robust forest fire smoke detection in complex environmentsNeural NetworksJun Wang, Chunman Yan4cites it
2025-12-31Multispectral remote sensing object detection via selective cross-modal interaction and aggregationNeural NetworksMinghao Cui, Jing Nie, Hanqing Sun et al.4cites it
2025-01-29Improving vehicle detection accuracy in complex traffic scenes through context attention and multi-scale feature fusion moduleApplied IntelligenceWenbo Liu, Binglin Zhao, Yuxin Zhu et al.3cites it
2025-11-03KSCNet: Exploring KAN and state space model collaboration network for small object detection from UAV imageryExpert Systems with ApplicationsYi Li, Huiying Xu, Yiming Sun et al.3cites it
2026-04-10EDA-Net: Efficient deformable attention network for aero-engine damage detection and recognitionExpert Systems with ApplicationsJujian Lv, Zhiqian Wang, 郭瑞银 et al.3cites it
2025-04-19Enhancing road safety with DL vision: Do driver distraction alerts hold the key?Neural Computing and ApplicationsLuqman Ali, Muhammed Swavaf, Fady S.K. Alnajjar et al.2cites it
2025-07-15TA-EnVODT: A cloud-edge integrated temporal-aware ensemble for real-time video object detection and tracking using knowledge projectionKnowledge-Based SystemsS K Sudha, S. Aji2cites it
2025-08-08MA-Neck: Mutual attention-based feature enhancement for lightweight object detectionPattern RecognitionDongxu Cheng, Hao Li, Zifang Zhou et al.2cites it
2025-06-24CurlObserver: A framework for curling trajectory detection and real-world mapping from broadcast videos with uncalibrated dynamic perspectivesExpert Systems with ApplicationsYanan Guo, Jing Jin, Hongyang Zhao et al.1cites it
2025-12-14NASSFG: Neural architecture search with saliency feature guidance for medical image object detectionExpert Systems with ApplicationsLiang Wang, Guocheng Ma, Yongjie Ma et al.1cites it
2026-04-13An integrated deep learning framework for effective management of surgical instruments tables based on videosHealth Care Management ScienceYong Ma, Tao Tao, Xuying Ma et al.1cites it
2026-06-25DQEF-Net: A dynamic quad-scale enhancement and fusion network for real-time drone detectionExpert Systems with ApplicationsQian Wan, Li Feng, Zhiwen Xiao et al.1cites it
2025-02-04MVSRF: Point cloud semantic segmentation and optimization method for granular construction objectsApplied IntelligenceLunhui Zhang, Guangjun Liu, Jiaqi Lu et al.0cites it
2025-10-31SPHEREA: Synthetic dataset generation for equirectangular panoramas of home environmentsKnowledge-Based SystemsKatarzyna Filus, Sebastian Pokuciński0cites it
2026-04-30Adaptive frequency modulated transformer for industrial surface defect detectionExpert Systems with ApplicationsLei Zhang, Xiaoqian Zhang, Zejun Huang et al.0cites it
2026-06-20ES-DETR: Real-time detection transformer with encover and soft-dropoutNeural NetworksYiqing He, Zefeng Zheng, Zhuowei Wang et al.0cites it
2026-06-27SAR image ship detection network based on quasi-gaussian convolution and pooling-gated mechanismExpert Systems with ApplicationsXuanran Peng, Chunman Yan0cites it
2026-07-30Multi-graph Cross Diffusion Attention Network for Alignment-free RGBT Video Object DetectionInternational Journal of Computer VisionQishun Wang, Zhengzheng Tu, Bo Jiang et al.0cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/zenodo-3908559

@misc{scholar4ai-code-zenodo-3908559,
  author = {{Scholar4AI}},
  title = {ultralytics/yolov5: v7.0 - YOLOv5 SOTA Realtime Instance Segmentation: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/zenodo-3908559}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).