smaranjitghose/corn-or-maize-leaf-disease-dataset: papers linking to it

Kaggle · www.kaggle.com/datasets/smaranjitghose/corn-or-maize-leaf-disease-dataset

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to smaranjitghose/corn-or-maize-leaf-disease-dataset (https://www.kaggle.com/datasets/smaranjitghose/corn-or-maize-leaf-disease-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 smaranjitghose/corn-or-maize-leaf-disease-dataset in their Crossref records, the first in 2024; most of them (2) in 2024.
By category: AI (3); the journals with the most are Expert Systems with Applications (1), Neural Computing and Applications (1) and Journal Of Big Data (1).

By year#

20242025

Papers linking to smaranjitghose/corn-or-maize-leaf-disease-dataset by publication year
Year	Papers
2024	2
2025	1

Journals#

Journals whose papers link to smaranjitghose/corn-or-maize-leaf-disease-dataset most
Journal	Papers
Expert Systems with Applications	1
Neural Computing and Applications	1
Journal Of Big Data	1

Papers linking to smaranjitghose/corn-or-maize-leaf-disease-dataset, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-08-10	Deep SqueezeNet learning model for diagnosis and prediction of maize leaf diseases	Journal Of Big Data	Prasannavenkatesan Theerthagiri, A. Usha Ruby, J. George Chellin Chandran et al.	61	cites it
2025-06-27	AgriTL-ViT: A Vision Transformer model with attention techniques for classification of plant leaf disease	Expert Systems with Applications	Meenakshi Srivastava, Varsha Sisaudia, Jasraj Meena	20	cites it
2024-05-22	EAMultiRes-DSPP: an efficient attention-based multi-residual network with dilated spatial pyramid pooling for identifying plant disease	Neural Computing and Applications	Mehdhar S. A. M. Al-Gaashani, Ammar Muthanna, Samia Allaoua Chelloug et al.	18	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). smaranjitghose/corn-or-maize-leaf-disease-dataset: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-smaranjitghose-corn-or-maize-leaf-disease-dataset

@misc{scholar4ai-code-kaggle-smaranjitghose-corn-or-maize-leaf-disease-dataset,
  author = {{Scholar4AI}},
  title = {smaranjitghose/corn-or-maize-leaf-disease-dataset: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-smaranjitghose-corn-or-maize-leaf-disease-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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