vipoooool/new-plant-diseases-dataset: papers linking to it

Kaggle · www.kaggle.com/datasets/vipoooool/new-plant-diseases-dataset

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Research papers in the 480 tracked journals that link to vipoooool/new-plant-diseases-dataset (https://www.kaggle.com/datasets/vipoooool/new-plant-diseases-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#

4 papers in the tracked journals link to the Kaggle dataset vipoooool/new-plant-diseases-dataset in their Crossref records, the first in 2021; most of them (2) in 2024.
By category: AI (4); the journals with the most are Cognitive Computation (1), Expert Systems with Applications (1) and Neural Computing and Applications (1).

By year#

20212025

Papers linking to vipoooool/new-plant-diseases-dataset by publication year
Year	Papers
2021	1
2024	2
2025	1

Journals#

Journals whose papers link to vipoooool/new-plant-diseases-dataset most
Journal	Papers
Cognitive Computation	1
Expert Systems with Applications	1
Neural Computing and Applications	1
Knowledge and Information Systems	1

Papers linking to vipoooool/new-plant-diseases-dataset, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-02-21	Automated weather forecasting and field monitoring using GRU-CNN model along with IoT to support precision agriculture	Expert Systems with Applications	T. Akilan, K. M. Baalamurugan	75	cites it
2021-09-01	Multilevel thresholding segmentation of color plant disease images using metaheuristic optimization algorithms	Neural Computing and Applications	Rüştü Akay, Radhwan A. A. Saleh, Shawqi Mohammed Farea et al.	26	cites it
2024-07-22	An adaptive and late multifusion framework in contextual representation based on evidential deep learning and Dempster–Shafer theory	Knowledge and Information Systems	Doaa Mohey El-Din, Aboul Ella Hassanein, Ehab E. Hassanien	13	cites it
2025-11-01	Auto-Encoded Attention Artificial Protozoa Convolutional Neural Networks with Few-Shot Learning for Plant Disease Detection	Cognitive Computation	Binal Upadhyay, Amit P Ganatra	0	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). vipoooool/new-plant-diseases-dataset: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-vipoooool-new-plant-diseases-dataset

@misc{scholar4ai-code-kaggle-vipoooool-new-plant-diseases-dataset,
  author = {{Scholar4AI}},
  title = {vipoooool/new-plant-diseases-dataset: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-vipoooool-new-plant-diseases-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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