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

fastai/imagenette: papers linking to it

GitHub · 1,140 stars · 77 forks · Jupyter Notebook · license Apache-2.0 · created 2019 · github.com/fastai/imagenette

← Code and data repositories cited in research papers

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

Share: X LinkedIn Bluesky Threads Facebook Reddit Hacker News Hatena LINE Email
Copy:

Key findings#

  • 23 papers in the tracked journals link to the GitHub repository fastai/imagenette in their Crossref records, the first in 2021; most of them (9) in 2025.
  • By category: AI (23); the journals with the most are Neural Networks (8), Pattern Recognition (5) and Neural Computing and Applications (2).

By year#

2021: 1 paper2022: 2 papers2023: 2 papers2024: 3 papers2025: 9 papers2026: 6 papers
20212026
Papers linking to fastai/imagenette by publication year
YearPapers
20211
20222
20232
20243
20259
20266

Journals#

Papers linking to fastai/imagenette, most cited first
PublishedTitleJournalAuthorsCitationsLink
2021-07-28Towards robust explanations for deep neural networksPattern RecognitionAnn-Kathrin Dombrowski, Christopher J. Anders, Klaus‐Robert Müller et al.49cites it
2022-08-15Interpretable Artificial Intelligence through Locality Guided Neural NetworksNeural NetworksRandy Tan, Lei Gao, Naimul Khan et al.19cites it
2022-04-13FocusNet: Classifying better by focusing on confusing classesPattern RecognitionXue Zhang, Zehua Sheng, Hui‐Liang Shen13cites it
2024-05-17Regional Adversarial Training for Better Robust GeneralizationInternational Journal of Computer VisionChuanbiao Song, Yanbo Fan, Aoyang Zhou et al.13cites it
2023-08-28Improving image classification of one-dimensional convolutional neural networks using Hilbert space-filling curvesApplied IntelligenceBert Verbruggen, Vincent Ginis11cites it
2024-06-19Improving interpretability via regularization of neural activation sensitivityMachine LearningOfir Moshe, Gil Fidel, Ron Bitton et al.9cites it
2023-11-17Topological structure of complex predictionsNature Machine IntelligenceMeng Liu, Tamal K. Dey, David F. Gleich8cites it
2025-05-16Evaluation and analysis of visual methods for CNN explainability: a novel approach and experimental studyNeural Computing and ApplicationsAndrei Dugăeșescu, Adina Magda Florea7cites it
2025-06-06Rect-ViT: Rectified attention via feature attribution can improve the adversarial robustness of Vision TransformersNeural NetworksXu Kang, Bin Song4cites it
2025-06-23Image Captions are Natural Prompts for Training Data SynthesisInternational Journal of Computer VisionShiye Lei, Hao Chen, Sen Zhang et al.4cites it
2025-07-15Capsule networks do not need to model everythingPattern RecognitionRiccardo Renzulli, Enzo Tartaglione, Marco Grangetto3cites it
2026-01-09A novel backpropagation algorithm based on negated kurtosis loss for training shallow, convolutional, and deep neural networksNeural NetworksEngin Cemal Mengüç, Alper Emlek, Danilo P. Mandic3cites it
2026-06-04Temperature-free loss function for contrastive learningNeural NetworksBum Jun Kim, Sang‐Woo Kim3cites it
2025-11-27FedPAD: Aggregation-free federated learning with prototype-based adaptive distillationKnowledge-Based SystemsTao Zhong, Kaiyan Zhao, Steve Drew et al.2cites it
2026-05-29DPC: Dynamic purification chain for adaptive adversarial defenseNeural NetworksZeshan Pang, Yuyuan Sun, Rongtao Liao et al.2cites it
2024-03-28Learn & drop: fast learning of cnns based on layer droppingNeural Computing and ApplicationsGiorgio Cruciata, Luca Cruciata, Liliana Lo Presti et al.1cites it
2025-03-25Online dimensionality reduction through stacked generalization of spectral methods with deep networksMachine LearningJuan Carlos Alvarado‐Pérez, Miguel Ángel García, Domènec Puig1cites it
2025-07-28Lossless steganographic network via model arithmetic operationsNeural NetworksYao Fan, Fuqiang Di, Mingqing Zhang et al.1cites it
2025-08-05BCVR: Bootstrap Clustering with Variance Regularization and Covariance Contrast for Self-supervised LearningKnowledge-Based SystemsCong Guo, Kan Ren, Qian Chen1cites it
2025-11-01BAM: Backdoor defense based on adversarial mitigationPattern RecognitionRun Lu, Peipeng Yu, Zhitao Huang et al.1cites it
2026-04-06PGMM: Prior Guided Multi-expert Model for Long-tailed ClassificationPattern RecognitionChenxun Deng, Lin Ji, Chengyang Zhang et al.1cites it
2026-03-28Contrast sensitivity in multimodal large language models: A psychophysics-inspired evaluationNeural NetworksPablo Hernández-Cámara, Alexandra Gomez-Villa, José Manuel Jaén-Lorites et al.0cites it
2026-05-16Stochastic approximation to contrastive learningNeural NetworksErland Brandser Olsson, Zhirong Yang0cites 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). fastai/imagenette: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-fastai-imagenette

@misc{scholar4ai-code-github-fastai-imagenette,
  author = {{Scholar4AI}},
  title = {fastai/imagenette: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-fastai-imagenette}},
  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).