wkentaro/labelme: papers linking to it

GitHub · 16,255 stars · 3,721 forks · Python · license GPL-3.0 · created 2016 · github.com/wkentaro/labelme

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to wkentaro/labelme (https://github.com/wkentaro/labelme), 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.

Key findings#

9 papers in the tracked journals link to the GitHub repository wkentaro/labelme in their Crossref records, the first in 2020; most of them (2) in 2025.
By category: AI (9); the journals with the most are Neural Computing and Applications (2), Expert Systems with Applications (2) and International Journal of Computer Vision (2).

By year#

20202025

Papers linking to wkentaro/labelme by publication year
Year	Papers
2020	1
2021	1
2022	2
2023	1
2024	2
2025	2

Journals#

Journals whose papers link to wkentaro/labelme most
Journal	Papers
Neural Computing and Applications	2
Expert Systems with Applications	2
International Journal of Computer Vision	2
Pattern Recognition	1
Nature Machine Intelligence	1

Papers linking to wkentaro/labelme, most cited first
Published	Title	Journal	Authors	Citations	Link
2020-11-09	Self-supervised retinal thickness prediction enables deep learning from unlabelled data to boost classification of diabetic retinopathy	Nature Machine Intelligence	Olle Holmberg, Niklas Köhler, Thiago Gonçalves dos Santos Martins et al.	88	cites it
2025-03-12	Deep learning for iris recognition: a review	Neural Computing and Applications	Yimin Yin, Siliang He, Renye Zhang et al.	29	cites it
2022-08-10	Feature decomposition and enhancement for unsupervised medical ultrasound image denoising and instance segmentation	Applied Intelligence	Tian-Tian Zhang, Hua Shu, Kam-Yiu Lam et al.	17	cites it
2021-09-14	Semantic Bottlenecks: Quantifying and Improving Inspectability of Deep Representations	International Journal of Computer Vision	Max Losch, Mario Fritz, Bernt Schiele	12	cites it
2024-05-11	Iron ore pellets measurement using deep learning based on YOLACT	Neural Computing and Applications	Caio Mario Carletti Vilela Santos, Ricardo de Almeida, Carlos Valadão et al.	6	cites it
2023-01-01	Data, Language and Graph-Based Reasoning Methods for Identification of Human Malicious Behaviors in Nuclear Security	Expert Systems with Applications	Zhan Li, Xingyu Song, Shi Chen et al.	5	cites it
2022-03-07	Graph-based modelling of superpixels for automatic identification of empty shelves in supermarkets	Pattern Recognition	Bikash Santra, Udita Ghosh, Dipti Prasad Mukherjee	4	cites it
2024-01-30	Spatially-Varying Illumination-Aware Indoor Harmonization	International Journal of Computer Vision	Zhongyun Hu, Jiahao Li, Xue Wang et al.	4	cites it
2025-07-15	Edge-Cloud deep learning computing for detecting heart failure with preserved ejection fraction on cardiac ultrasound	Expert Systems with Applications	Tse-Hsien Lu, Wu‐Chun Chung, Chung‐Lieh Hung et al.	2	cites 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). wkentaro/labelme: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-wkentaro-labelme

@misc{scholar4ai-code-github-wkentaro-labelme,
  author = {{Scholar4AI}},
  title = {wkentaro/labelme: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-wkentaro-labelme}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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