---
title: "DeepQuestAI/Fire-Smoke-Dataset: papers citing it"
description: "3 papers in the tracked journals link to the GitHub repository DeepQuestAI/Fire-Smoke-Dataset in their Crossref records, the first in 2021; most of them (2) in 2024."
url: https://scholar4ai.com/code/github-deepquestai-fire-smoke-dataset
markdown_url: https://scholar4ai.com/code/github-deepquestai-fire-smoke-dataset.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to the GitHub repository DeepQuestAI/Fire-Smoke-Dataset in their Crossref records, the first in 2021; most of them (2) in 2024. (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)
---

# DeepQuestAI/Fire-Smoke-Dataset: papers linking to it

Research papers in the 480 tracked journals that link to DeepQuestAI/Fire-Smoke-Dataset (https://github.com/DeepQuestAI/Fire-Smoke-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.

- GitHub
- 148 stars
- 51 forks
- Jupyter Notebook
- created 2019
- https://github.com/DeepQuestAI/Fire-Smoke-Dataset

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

## Key findings

- 3 papers in the tracked journals link to the GitHub repository DeepQuestAI/Fire-Smoke-Dataset in their Crossref records, the first in 2021; most of them (2) in 2024.
- By category: AI (3); the journals with the most are Expert Systems with Applications (2) and Pattern Recognition (1).
- 3 of the papers build on one another: a later paper cites an earlier one that also links DeepQuestAI/Fire-Smoke-Dataset.

## By year

*Papers linking to DeepQuestAI/Fire-Smoke-Dataset by publication year*

| Year | Papers |
|---|---:|
| 2021 | 1 |
| 2024 | 2 |

## Journals

*Journals whose papers link to DeepQuestAI/Fire-Smoke-Dataset most*

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 |
| [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Attention based CNN model for fire detection and localization in real-world images](https://doi.org/10.1016/j.eswa.2021.116114) (Expert Systems with Applications, 2021)
  - [Fire and smoke detection from videos: A literature review under a novel taxonomy](https://doi.org/10.1016/j.eswa.2024.124783) (Expert Systems with Applications, 2024) — cites the paper above
  - [Optimized cross-module attention network and medium-scale dataset for effective fire detection](https://doi.org/10.1016/j.patcog.2024.111273) (Pattern Recognition, 2024) — cites the paper above

## Papers

*Papers linking to DeepQuestAI/Fire-Smoke-Dataset, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2021-10-26 | [Attention based CNN model for fire detection and localization in real-world images](https://doi.org/10.1016/j.eswa.2021.116114) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Saima Majid, Fayadh S. Alenezi, Sarfaraz Masood et al. | 256 | cites it |
| 2024-07-14 | [Fire and smoke detection from videos: A literature review under a novel taxonomy](https://doi.org/10.1016/j.eswa.2024.124783) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Diego Gragnaniello, Antonio Greco, Carlo Sansone et al. | 77 | cites it |
| 2024-12-10 | [Optimized cross-module attention network and medium-scale dataset for effective fire detection](https://doi.org/10.1016/j.patcog.2024.111273) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Zulfiqar Ahmad Khan, Fath U Min Ullah, Hikmat Yar et al. | 23 | 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). DeepQuestAI/Fire-Smoke-Dataset: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-deepquestai-fire-smoke-dataset

```bibtex
@misc{scholar4ai-code-github-deepquestai-fire-smoke-dataset,
  author = {{Scholar4AI}},
  title = {DeepQuestAI/Fire-Smoke-Dataset: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-deepquestai-fire-smoke-dataset}},
  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/).