---
title: "alessiocorrado99/animals10: papers citing this dataset"
description: "5 papers in the tracked journals link to the Kaggle dataset alessiocorrado99/animals10 in their Crossref records, the first in 2022; most of them (3) in 2023."
url: https://scholar4ai.com/code/kaggle-alessiocorrado99-animals10
markdown_url: https://scholar4ai.com/code/kaggle-alessiocorrado99-animals10.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to the Kaggle dataset alessiocorrado99/animals10 in their Crossref records, the first in 2022; most of them (3) in 2023. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# alessiocorrado99/animals10: papers linking to it

Research papers in the 480 tracked journals that link to alessiocorrado99/animals10 (https://www.kaggle.com/datasets/alessiocorrado99/animals10), 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.

- Kaggle
- https://www.kaggle.com/datasets/alessiocorrado99/animals10

All repositories: https://scholar4ai.com/code.md

## Key findings

- 5 papers in the tracked journals link to the Kaggle dataset alessiocorrado99/animals10 in their Crossref records, the first in 2022; most of them (3) in 2023.
- By category: AI (5); the journals with the most are Artificial Intelligence Review (1), Information Fusion (1) and Expert Systems with Applications (1).

## By year

*Papers linking to alessiocorrado99/animals10 by publication year*

| Year | Papers |
|---|---:|
| 2022 | 1 |
| 2023 | 3 |
| 2026 | 1 |

## Journals

*Journals whose papers link to alessiocorrado99/animals10 most*

| Journal | Papers |
|---|---:|
| [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 1 |
| [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | 1 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 1 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 1 |

## Papers

*Papers linking to alessiocorrado99/animals10, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2023-06-19 | [WSDS-GAN: A weak-strong dual supervised learning method for underwater image enhancement](https://doi.org/10.1016/j.patcog.2023.109774) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Qiong Liu, Qi Zhang, Wei Liu et al. | 66 | cites it |
| 2023-06-20 | [Integrated animal monitoring system with animal detection and classification capabilities: a review on image modality, techniques, applications, and challenges](https://doi.org/10.1007/s10462-023-10534-z) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | N. Sundaram, Divya Meena Sundaram | 23 | cites it |
| 2023-06-01 | [Hybrid image analysis model for hashtag recommendation through the use of deep learning methods](https://doi.org/10.1016/j.eswa.2023.120566) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Dawid Połap | 16 | cites it |
| 2022-04-18 | [Defense against adversarial examples based on wavelet domain analysis](https://doi.org/10.1007/s10489-022-03159-2) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Armaghan Sarvar, Maryam Amirmazlaghani | 11 | cites it |
| 2026-06-25 | [Basic belief assignment determination based on contrastive learning for pattern classification](https://doi.org/10.1016/j.inffus.2026.104572) | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | Wei Li, Deqiang Han, Jean Dezert 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). alessiocorrado99/animals10: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-alessiocorrado99-animals10

```bibtex
@misc{scholar4ai-code-kaggle-alessiocorrado99-animals10,
  author = {{Scholar4AI}},
  title = {alessiocorrado99/animals10: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-alessiocorrado99-animals10}},
  urldate = {2026-11-03},
  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/).