---
title: "Caltech-101 / 256: research papers using this data"
description: "From Nov 2023 to Oct 2026, 116 archived papers mentioned Caltech-101 / 256 in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Aug 2024 (7)."
url: https://scholar4ai.com/datasets/caltech-101-256
markdown_url: https://scholar4ai.com/datasets/caltech-101-256.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "From Nov 2023 to Oct 2026, 116 archived papers mentioned Caltech-101 / 256 in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Aug 2024 (7). (as of 2026-11-05)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-05T06:02:37+09:00
window: 2026-10-07 to 2026-11-05
source: OpenAlex (CC0)
---

# Caltech-101 / 256

[Browse dataset profiles](https://scholar4ai.com/datasets/directory.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: Caltech-101, Caltech-256, Caltech101, Caltech256

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, 116 archived papers mentioned Caltech-101 / 256 in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Aug 2024 (7).
- Caltech-101 / 256 was mentioned in 2 papers in the last 30 days (2026-10-07 to 2026-11-05), ranking #127 of the 246 datasets mentioned.
- By journal category: AI (2).
- Most of them appeared in International Journal of Computer Vision (1) and Information Processing & Management (1).
- From 2017 to 2026 (so far), Caltech-101 / 256 was mentioned in 147 papers in the tracked journals, most of them in AI (145), information systems (1) and operations research (1).
- 32 of them were published in 2025, against 2 in 2017.
- Since 2023, the institutions with the most of these papers were Chinese Academy of Sciences (7), Chinese University of Hong Kong (6) and Institute of Automation (6).
- The journals publishing most of them were IEEE Transactions on Pattern Analysis and Machine Intelligence (25), International Journal of Computer Vision (18) and IEEE Transactions on Neural Networks and Learning Systems (14).
- The most-cited of them is “A review of convolutional neural networks in computer vision” (Artificial Intelligence Review, 2024), with 1,187 citations.
- Papers use Caltech-101 / 256 most often with ImageNet (91), CIFAR-10 / CIFAR-100 (67) and MNIST / Fashion-MNIST (50); it has 25 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 |
|---|---:|---:|---:|---:|
|  | 42 | 38 | 36 | 116 |

## 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) | 2 | 5 | 3 | 3 | 5 | 2 | 15 | 47 | 30 | 33 |
| [Information Systems](https://scholar4ai.com/categories/information-systems.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
| [Operations Research](https://scholar4ai.com/categories/operations-research.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
| All categories | 2 | 5 | 3 | 3 | 5 | 2 | 15 | 47 | 32 | 33 |

## 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) | 25 |
| 2 | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | 18 |
| 3 | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 14 |
| 4 | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 10 |
| 5 | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 8 |
| 6 | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 7 |
| 7 | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 7 |
| 8 | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 6 |
| 9 | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 4 |
| 10 | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 4 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 7 |
| 2 | [Chinese University of Hong Kong](https://scholar4ai.com/institutions/chinese-university-of-hong-kong.md) | 6 |
| 3 | [Institute of Automation](https://scholar4ai.com/institutions/institute-of-automation.md) | 6 |
| 4 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 6 |
| 5 | [University of Electronic Science and Technology of China](https://scholar4ai.com/institutions/university-of-electronic-science-and-technology-of-china.md) | 6 |
| 6 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 6 |
| 7 | [Hong Kong University of Science and Technology](https://scholar4ai.com/institutions/hong-kong-university-of-science-and-technology.md) | 5 |
| 8 | [Harbin Institute of Technology](https://scholar4ai.com/institutions/harbin-institute-of-technology.md) | 4 |
| 9 | [Nanjing University](https://scholar4ai.com/institutions/nanjing-university.md) | 4 |
| 10 | [University of Chinese Academy of Sciences](https://scholar4ai.com/institutions/university-of-chinese-academy-of-sciences.md) | 4 |

*Countries with the most papers, since 2023*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 72 |
| 2 | Hong Kong | 18 |
| 3 | United States | 18 |
| 4 | Australia | 17 |
| 5 | United Kingdom | 12 |
| 6 | South Korea | 8 |
| 7 | Singapore | 6 |
| 8 | Germany | 5 |
| 9 | France | 5 |
| 10 | India | 5 |

*Keywords with the most papers, since 2023*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [image classification](https://scholar4ai.com/keywords/image-classification.md) | 20 |
| 2 | [vision-language models](https://scholar4ai.com/keywords/vision-language-models.md) | 16 |
| 3 | CLIP | 14 |
| 4 | [transfer learning](https://scholar4ai.com/keywords/transfer-learning.md) | 12 |
| 5 | [domain generalization](https://scholar4ai.com/keywords/domain-generalization.md) | 11 |
| 6 | [domain adaptation](https://scholar4ai.com/keywords/domain-adaptation.md) | 9 |
| 7 | [catastrophic forgetting](https://scholar4ai.com/keywords/catastrophic-forgetting.md) | 8 |
| 8 | domain shift | 8 |
| 9 | spiking neural networks | 8 |
| 10 | [convolutional neural networks](https://scholar4ai.com/keywords/convolutional-neural-networks.md) | 7 |

## Most-cited papers

*Most-cited papers since 2017*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 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. |
| 2 | 998 | 30.9 | [Vision-Language Models for Vision Tasks: A Survey](https://doi.org/10.1109/tpami.2024.3369699) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2024-02-26 | Jingyi Zhang, Jiaxing Huang, Sheng Jin et al. |
| 3 | 613 | 18.5 | [Autoencoders and their applications in machine learning: a survey](https://doi.org/10.1007/s10462-023-10662-6) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 2024-02-03 | Kamal Berahmand, Fatemeh Daneshfar, Elaheh Sadat Salehi et al. |
| 4 | 254 | 3.0 | [Effects of Image Degradation and Degradation Removal to CNN-Based Image Classification](https://doi.org/10.1109/tpami.2019.2950923) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2019-11-01 | Yanting Pei, Yaping Huang, Qi Zou et al. |
| 5 | 243 | 8.6 | [Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark](https://doi.org/10.1109/tpami.2024.3418862) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 2024-06-25 | Wenke Huang, Mang Ye, Zekun Shi et al. |

## Used together with

Papers use Caltech-101 / 256 most often with ImageNet (91), CIFAR-10 / CIFAR-100 (67) and MNIST / Fashion-MNIST (50); it has 25 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

*What papers use Caltech-101 / 256 together with (at least 3 papers; lift 1 = chance)*

| Used with | Type | Papers using both | Lift |
|---|---|---:|---:|
| [ImageNet](https://scholar4ai.com/datasets/imagenet.md) | Dataset | 91 | 12.5 |
| [CIFAR-10 / CIFAR-100](https://scholar4ai.com/datasets/cifar-10-cifar-100.md) | Dataset | 67 | 15.6 |
| [MNIST / Fashion-MNIST](https://scholar4ai.com/datasets/mnist-fashion-mnist.md) | Dataset | 50 | 14.6 |
| [Fine-grained benchmarks (CUB-200, Stanford Cars, Oxford Flowers)](https://scholar4ai.com/datasets/fine-grained-benchmarks-cub-200-stanford-cars-oxford-flowers.md) | Dataset | 33 | 46.6 |
| [PASCAL VOC](https://scholar4ai.com/datasets/pascal-voc.md) | Dataset | 29 | 28.1 |
| [SVHN](https://scholar4ai.com/datasets/svhn.md) | Dataset | 27 | 41.8 |
| [Action recognition (Kinetics, UCF101, HMDB51)](https://scholar4ai.com/datasets/action-recognition-kinetics-ucf101-hmdb51.md) | Dataset | 24 | 26.8 |
| [Domain adaptation benchmarks (Office-31, Office-Home, VisDA…](https://scholar4ai.com/datasets/domain-adaptation-benchmarks-office-31-office-home-visda-domainnet.md) | Dataset | 24 | 47.6 |
| [MS COCO](https://scholar4ai.com/datasets/ms-coco.md) | Dataset | 22 | 7.7 |
| [Face recognition (LFW, CelebA, VGGFace2)](https://scholar4ai.com/datasets/face-recognition-lfw-celeba-vggface2.md) | Dataset | 7 | 7.7 |
| [Cityscapes](https://scholar4ai.com/datasets/cityscapes.md) | Dataset | 6 | 6.5 |
| [Kaggle](https://scholar4ai.com/datasets/kaggle.md) | Dataset | 6 | 3.4 |

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

## Papers

*Papers mentioning Caltech-101 / 256 in the last 30 days, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-26 | [TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation](https://doi.org/10.1007/s11263-026-03081-x) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Haokun Lin, Teng Wang, Yixiao Ge et al. | City University of Hong Kong; Chinese Academy of Sciences; Tencent (China); … |
| 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 |

## Cite this page

Scholar4AI. (2026). Caltech-101 / 256. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/caltech-101-256

```bibtex
@misc{scholar4ai-datasets-caltech-101-256,
  author = {{Scholar4AI}},
  title = {Caltech-101 / 256},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/caltech-101-256}},
  urldate = {2026-11-05},
  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/).