---
title: "CIFAR-10 / CIFAR-100: research papers using this data"
description: "From Nov 2023 to Oct 2026, 1,005 archived papers mentioned CIFAR-10 / CIFAR-100 in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jan 2025 (49)."
url: https://scholar4ai.com/datasets/cifar-10-cifar-100
markdown_url: https://scholar4ai.com/datasets/cifar-10-cifar-100.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "From Nov 2023 to Oct 2026, 1,005 archived papers mentioned CIFAR-10 / CIFAR-100 in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jan 2025 (49). (as of 2026-11-04)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-04T18:03:26+09:00
window: 2026-10-06 to 2026-11-04
source: OpenAlex (CC0)
---

# CIFAR-10 / CIFAR-100

[Browse dataset profiles](https://scholar4ai.com/datasets/directory/page/2.md)

Labelled image collections used to train and compare image classifiers.

- data category: Image classification benchmarks
- 0 papers in the last 7 days
- Names searched for: CIFAR, CIFAR10, CIFAR100

Most-used data: https://scholar4ai.com/rankings/datasets.md · All Image classification benchmarks datasets: https://scholar4ai.com/datasets/image-classification-benchmarks.md



## Key findings

- From Nov 2023 to Oct 2026, 1,005 archived papers mentioned CIFAR-10 / CIFAR-100 in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jan 2025 (49).
- CIFAR-10 / CIFAR-100 was mentioned in 15 papers in the last 30 days (2026-10-06 to 2026-11-04), ranking #11 of the 255 datasets mentioned.
- By journal category: AI (15).
- Most of them appeared in Neural Networks (4), Pattern Recognition (4) and Knowledge-Based Systems (3).
- From 2017 to 2026 (so far), CIFAR-10 / CIFAR-100 was mentioned in 1,383 papers in the tracked journals, most of them in AI (1,338), operations research (24) and information systems (12).
- 334 of them were published in 2025, against 6 in 2017.
- Since 2023, the institutions with the most of these papers were Chinese Academy of Sciences (66), Nanyang Technological University (43) and University of Chinese Academy of Sciences (37).
- The journals publishing most of them were IEEE Transactions on Pattern Analysis and Machine Intelligence (169), IEEE Transactions on Neural Networks and Learning Systems (160) and Neural Networks (92).
- The most-cited of them is “Res2Net: A New Multi-Scale Backbone Architecture” (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019), with 3,404 citations.
- Papers use CIFAR-10 / CIFAR-100 most often with ImageNet (792), MNIST / Fashion-MNIST (540) and SVHN (178); it has 87 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

## Mentions over 36 months

*Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)*

| Trend | Nov 23–Oct 24 | Nov 24–Oct 25 | Nov 25–Oct 26 | 36 months |
|---|---:|---:|---:|---:|
|  | 392 | 353 | 260 | 1,005 |

## Papers per year

*Papers per publication year and category*

| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
| [AI](https://scholar4ai.com/categories/ai.md) | 6 | 19 | 29 | 39 | 75 | 105 | 154 | 376 | 322 | 213 |
| [Operations Research](https://scholar4ai.com/categories/operations-research.md) | 0 | 0 | 0 | 1 | 0 | 0 | 2 | 7 | 9 | 5 |
| [Information Systems](https://scholar4ai.com/categories/information-systems.md) | 0 | 1 | 0 | 0 | 0 | 1 | 4 | 2 | 3 | 1 |
| [Statistics](https://scholar4ai.com/categories/statistics.md) | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 2 | 0 | 1 |
| [Higher Education and Research](https://scholar4ai.com/categories/higher-education-and-research.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 |
| [Finance](https://scholar4ai.com/categories/finance.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 |
| All categories | 6 | 20 | 29 | 40 | 76 | 106 | 161 | 390 | 334 | 221 |

## Where the papers come from

*Journals with the most papers, since 2023*

| # | Journal | Papers |
|---:|---|---:|
| 1 | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 169 |
| 2 | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 160 |
| 3 | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 92 |
| 4 | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 70 |
| 5 | [IEEE Transactions on Artificial Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-artificial-intelligence.md) | 70 |
| 6 | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 69 |
| 7 | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 64 |
| 8 | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | 64 |
| 9 | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 60 |
| 10 | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 42 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 66 |
| 2 | [Nanyang Technological University](https://scholar4ai.com/institutions/nanyang-technological-university.md) | 43 |
| 3 | [University of Chinese Academy of Sciences](https://scholar4ai.com/institutions/university-of-chinese-academy-of-sciences.md) | 37 |
| 4 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 37 |
| 5 | [Institute of Automation](https://scholar4ai.com/institutions/institute-of-automation.md) | 34 |
| 6 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 29 |
| 7 | [University of Electronic Science and Technology of China](https://scholar4ai.com/institutions/university-of-electronic-science-and-technology-of-china.md) | 28 |
| 8 | [Sun Yat-sen University](https://scholar4ai.com/institutions/sun-yat-sen-university.md) | 27 |
| 9 | [Xidian University](https://scholar4ai.com/institutions/xidian-university.md) | 27 |
| 10 | [Harbin Institute of Technology](https://scholar4ai.com/institutions/harbin-institute-of-technology.md) | 23 |

*Countries with the most papers, since 2023*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 536 |
| 2 | United States | 164 |
| 3 | United Kingdom | 121 |
| 4 | Australia | 99 |
| 5 | Hong Kong | 83 |
| 6 | Singapore | 77 |
| 7 | Italy | 56 |
| 8 | South Korea | 46 |
| 9 | Canada | 39 |
| 10 | Germany | 36 |

*Keywords with the most papers, since 2023*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [image classification](https://scholar4ai.com/keywords/image-classification.md) | 171 |
| 2 | CIFAR-10 | 70 |
| 3 | [federated learning](https://scholar4ai.com/keywords/federated-learning.md) | 67 |
| 4 | [convolutional neural networks](https://scholar4ai.com/keywords/convolutional-neural-networks.md) | 66 |
| 5 | [catastrophic forgetting](https://scholar4ai.com/keywords/catastrophic-forgetting.md) | 63 |
| 6 | [knowledge distillation](https://scholar4ai.com/keywords/knowledge-distillation.md) | 57 |
| 7 | neural architecture search | 56 |
| 8 | [adversarial robustness](https://scholar4ai.com/keywords/adversarial-robustness.md) | 55 |
| 9 | continual learning | 54 |
| 10 | spiking neural networks | 48 |

## Most-cited papers

*Most-cited papers since 2017*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 3,404 | 39.5 | [Res2Net: A New Multi-Scale Backbone Architecture](https://doi.org/10.1109/tpami.2019.2938758) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2019-08-30 | Shanghua Gao, Ming‐Ming Cheng, Kai Zhao et al. |
| 2 | 3,086 | 31.1 | [A systematic study of the class imbalance problem in convolutional neural networks](https://doi.org/10.1016/j.neunet.2018.07.011) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 2018-07-29 | Mateusz Buda, Atsuto Maki, Maciej A. Mazurowski |
| 3 | 2,861 | 28.8 | [Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning](https://doi.org/10.1109/tpami.2018.2858821) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2018-07-23 | Takeru Miyato, Shin‐ichi Maeda, Masanori Koyama et al. |
| 4 | 2,404 | 25.6 | [One Pixel Attack for Fooling Deep Neural Networks](https://doi.org/10.1109/tevc.2019.2890858) | [IEEE Transactions on Evolutionary Computation](https://scholar4ai.com/journals/ieee-transactions-on-evolutionary-computation.md) | 2019-01-04 | Jiawei Su, Danilo Vasconcellos Vargas, Kouichi Sakurai |
| 5 | 1,187 | 37.8 | [A review of convolutional neural networks in computer vision](https://doi.org/10.1007/s10462-024-10721-6) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 2024-03-23 | Xia Zhao, Limin Wang, Yufei Zhang et al. |

## Used together with

Papers use CIFAR-10 / CIFAR-100 most often with ImageNet (792), MNIST / Fashion-MNIST (540) and SVHN (178); it has 87 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

*What papers use CIFAR-10 / CIFAR-100 together with (at least 3 papers; lift 1 = chance)*

| Used with | Type | Papers using both | Lift |
|---|---|---:|---:|
| [ImageNet](https://scholar4ai.com/datasets/imagenet.md) | Dataset | 792 | 11.6 |
| [MNIST / Fashion-MNIST](https://scholar4ai.com/datasets/mnist-fashion-mnist.md) | Dataset | 540 | 16.8 |
| [SVHN](https://scholar4ai.com/datasets/svhn.md) | Dataset | 178 | 29.4 |
| [MS COCO](https://scholar4ai.com/datasets/ms-coco.md) | Dataset | 116 | 4.3 |
| [Fine-grained benchmarks (CUB-200, Stanford Cars, Oxford Flowers)](https://scholar4ai.com/datasets/fine-grained-benchmarks-cub-200-stanford-cars-oxford-flowers.md) | Dataset | 104 | 15.7 |
| [Face recognition (LFW, CelebA, VGGFace2)](https://scholar4ai.com/datasets/face-recognition-lfw-celeba-vggface2.md) | Dataset | 69 | 8.1 |
| [Caltech-101 / 256](https://scholar4ai.com/datasets/caltech-101-256.md) | Dataset | 67 | 15.6 |
| [PASCAL VOC](https://scholar4ai.com/datasets/pascal-voc.md) | Dataset | 59 | 6.1 |
| [Kaggle](https://scholar4ai.com/datasets/kaggle.md) | Dataset | 39 | 2.3 |
| [IMDb](https://scholar4ai.com/datasets/imdb.md) | Dataset | 37 | 5.4 |
| [Cityscapes](https://scholar4ai.com/datasets/cityscapes.md) | Dataset | 35 | 4.1 |
| [Domain adaptation benchmarks (Office-31, Office-Home, VisDA…](https://scholar4ai.com/datasets/domain-adaptation-benchmarks-office-31-office-home-visda-domainnet.md) | Dataset | 35 | 7.4 |

The whole network: https://scholar4ai.com/code/network.md

## Papers

*Papers mentioning CIFAR-10 / CIFAR-100 in the last 30 days, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-28 | [Breathing life into activation functions: the SWIn framework for sustained nonlinearity](https://doi.org/10.1016/j.neunet.2026.109784) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Yu Ran, Li Zhang, Shi Yuan | University of Manchester; University of International Business and Economics |
| 2026-10-26 | [CARD: Conditional backdoor repair under limited clean data via target-side occupancy–takeover readout](https://doi.org/10.1016/j.eswa.2026.134869) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Yuchen Dong, Jian Peng, Lixu Sun et al. | Xinjiang University; Xinjiang Institute of Engineering |
| 2026-10-23 | [DFedSVRG: Decentralized federated learning with stochastic variance reduced gradient](https://doi.org/10.1016/j.eswa.2026.134838) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Jialong Huang, Jianhua Hu, Qinglun Li et al. | University of Shanghai for Science and Technology; National University of Defense Technology |
| 2026-10-23 | [A Lagrangian-inspired force-based loss for deep metric learning](https://doi.org/10.1016/j.neunet.2026.109798) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Byung Do Cheon, Jeongmin Yu, Jung-Eun Kim et al. | Yonsei University |
| 2026-10-23 | [Increment Vector Transformation for Class Incremental Learning](https://doi.org/10.1016/j.patcog.2026.115201) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Zihuan Qiu, Yi Xu, Fanman Meng et al. | University of Electronic Science and Technology of China |
| 2026-10-20 | [Central description length (CDL) clustering validation index](https://doi.org/10.1016/j.artint.2026.104644) | [Artificial Intelligence](https://scholar4ai.com/journals/artificial-intelligence.md) | Mahdi Shamsi, Soosan Beheshti | McGill University; Toronto Metropolitan University |
| 2026-10-19 | [Nothing beyond randomness is required for forward-forward learning](https://doi.org/10.1016/j.patcog.2026.115214) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Yue Zhou, Xiaofang Hu, Shukai Duan | Southwest University |
| 2026-10-15 | [Frequency–spatial dual-domain imperceptible watermarking for robust image datasets copyright protection](https://doi.org/10.1016/j.ipm.2026.105235) | [Information Processing & Management](https://scholar4ai.com/journals/information-processing-management.md) | Xiaojie Du, Yedi Chen, Kai Ma et al. | Guizhou Normal University |
| 2026-10-14 | [A transferable adversarial attack method via Loss Surface Guided Gradient Optimization](https://doi.org/10.1016/j.knosys.2026.117199) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Chuan Ye, Xiaoqing Yang, Yunhan Li et al. | Southwest Petroleum University; Sichuan University; Huzhou College |
| 2026-10-14 | [Dynamic gain neuromodulation attenuates stability gaps during continual joint training](https://doi.org/10.1016/j.neunet.2026.109767) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Alejandro Rodriguez-Garcia, Anindya Ghosh, Srikanth Ramaswamy | Newcastle University |
| 2026-10-13 | [Dual-prompt semantic decoupling and transfer for long-tailed recognition](https://doi.org/10.1016/j.neunet.2026.109753) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Xiaohua Chen, Yue Wang, Yanbiao Ma | Communication University of China; Xidian University; Renmin University of China |
| 2026-10-10 | [Variational graph-based semi-supervised learning](https://doi.org/10.1016/j.patcog.2026.115073) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Sebastian Salwig, Till Kahlke, Jörg Lücke | Universität Innsbruck |
| 2026-10-09 | [Semantic-Clustered Multimodal Prompt Tuning for long-tailed visual recognition](https://doi.org/10.1016/j.knosys.2026.117165) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Binlong Dong, Yuge Xu | South China University of Technology |
| 2026-10-08 | [Learning transferable noise recognizers from training dynamics for robust classification](https://doi.org/10.1016/j.patcog.2026.115112) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Mengyang Li, Shu Zhou, Jue Lv et al. | Tianjin Normal University |
| 2026-10-07 | [CGNC: Confidence-Guided Neighbor Consensus for semi-supervised learning](https://doi.org/10.1016/j.knosys.2026.117154) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Ahmed Abbas Jaber, Mengzi Tang, Zhishu Shen et al. | Wuhan University of Technology |

## Cite this page

Scholar4AI. (2026). CIFAR-10 / CIFAR-100. Journal and Conference Research Rankings. Retrieved November 4, 2026, from https://scholar4ai.com/datasets/cifar-10-cifar-100

```bibtex
@misc{scholar4ai-datasets-cifar-10-cifar-100,
  author = {{Scholar4AI}},
  title = {CIFAR-10 / CIFAR-100},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/cifar-10-cifar-100}},
  urldate = {2026-11-04},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).