minhhuy2810/rice-diseases-image-dataset: papers linking to it

Kaggle · www.kaggle.com/datasets/minhhuy2810/rice-diseases-image-dataset

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to minhhuy2810/rice-diseases-image-dataset (https://www.kaggle.com/datasets/minhhuy2810/rice-diseases-image-dataset), 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 minhhuy2810/rice-diseases-image-dataset in their Crossref records, the first in 2020; 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).

By year#

20202025

Papers linking to minhhuy2810/rice-diseases-image-dataset by publication year
Year	Papers
2020	1
2024	1
2025	1

Journals#

Journals whose papers link to minhhuy2810/rice-diseases-image-dataset most
Journal	Papers
Neural Computing and Applications	2
Artificial Intelligence Review	1

Papers linking to minhhuy2810/rice-diseases-image-dataset, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-11-18	Image-based rice leaf disease detection using CNN and generative adversarial network	Neural Computing and Applications	Syed Taha Yeasin Ramadan, Md Shafiqul Islam, Tanjim Sakib et al.	27	cites it
2020-05-28	Image classifiers and image deep learning classifiers evolved in detection of Oryza sativa diseases: survey	Artificial Intelligence Review	Goluguri N. V. Rajareddy, K. Suganya Devi, Nagesh Vadaparthi	26	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). minhhuy2810/rice-diseases-image-dataset: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-minhhuy2810-rice-diseases-image-dataset

@misc{scholar4ai-code-kaggle-minhhuy2810-rice-diseases-image-dataset,
  author = {{Scholar4AI}},
  title = {minhhuy2810/rice-diseases-image-dataset: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-minhhuy2810-rice-diseases-image-dataset}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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