shayanriyaz/riceleafs: papers linking to it

Kaggle · www.kaggle.com/datasets/shayanriyaz/riceleafs

← Code and data repositories cited in research papers

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

3 papers in the tracked journals link to the Kaggle dataset shayanriyaz/riceleafs in their Crossref records, the first in 2023; most of them (1) in 2025.
By category: AI (3); the journals with the most are Neural Computing and Applications (2) and Artificial Intelligence Review (1).
2 of the papers build on one another: a later paper cites an earlier one that also links shayanriyaz/riceleafs.

By year#

20232025

Papers linking to shayanriyaz/riceleafs by publication year
Year	Papers
2023	1
2024	1
2025	1

Journals#

Journals whose papers link to shayanriyaz/riceleafs most
Journal	Papers
Neural Computing and Applications	2
Artificial Intelligence Review	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Systematic study on deep learning-based plant disease detection or classification Artificial Intelligence Review, 2023
- Deep learning for recognition and detection of plant diseases and pests Neural Computing and Applications, 2025 — cites the paper above

Papers linking to shayanriyaz/riceleafs, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-06-14	Systematic study on deep learning-based plant disease detection or classification	Artificial Intelligence Review	C. K. Sunil, C. D. Jaidhar, Nagamma Patil	104	cites it
2024-07-29	Streamlining plant disease diagnosis with convolutional neural networks and edge devices	Neural Computing and Applications	Md. Faysal Ahamed, Abdus Salam, Md. Nahiduzzaman et al.	29	cites it
2025-03-12	Deep learning for recognition and detection of plant diseases and pests	Neural Computing and Applications	Xiang Yue, Kai Qi, Xinyi Na et al.	11	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). shayanriyaz/riceleafs: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-shayanriyaz-riceleafs

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

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