---
title: "state-farm-distracted-driver-detection: papers citing it"
description: "5 papers in the tracked journals link to the Kaggle dataset state-farm-distracted-driver-detection in their Crossref records, the first in 2020; most of them (2) in 2025."
url: https://scholar4ai.com/code/kaggle-competition-state-farm-distracted-driver-detection
markdown_url: https://scholar4ai.com/code/kaggle-competition-state-farm-distracted-driver-detection.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to the Kaggle dataset state-farm-distracted-driver-detection in their Crossref records, the first in 2020; most of them (2) in 2025. (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)
---

# state-farm-distracted-driver-detection: papers linking to it

Research papers in the 480 tracked journals that link to state-farm-distracted-driver-detection (https://www.kaggle.com/competitions/state-farm-distracted-driver-detection), 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.

- Kaggle
- https://www.kaggle.com/competitions/state-farm-distracted-driver-detection

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

## Key findings

- 5 papers in the tracked journals link to the Kaggle dataset state-farm-distracted-driver-detection in their Crossref records, the first in 2020; most of them (2) in 2025.
- By category: AI (5); the journals with the most are Expert Systems with Applications (2), Neural Computing and Applications (2) and Knowledge and Information Systems (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links state-farm-distracted-driver-detection.

## By year

*Papers linking to state-farm-distracted-driver-detection by publication year*

| Year | Papers |
|---|---:|
| 2020 | 1 |
| 2022 | 2 |
| 2025 | 2 |

## Journals

*Journals whose papers link to state-farm-distracted-driver-detection most*

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2 |
| [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [A deep learning-based driver distraction identification framework over edge cloud](https://doi.org/10.1007/s00521-020-05328-1) (Neural Computing and Applications, 2020)
  - [Cell phone usage detection in roadway images: from plate recognition to violation classification](https://doi.org/10.1007/s00521-022-07943-6) (Neural Computing and Applications, 2022) — cites the paper above

## Papers

*Papers linking to state-farm-distracted-driver-detection, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-09-14 | [A deep learning-based driver distraction identification framework over edge cloud](https://doi.org/10.1007/s00521-020-05328-1) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Abdu Gumaei, Mabrook S. Al-Rakhami, Mohammad Mehedi Hassan et al. | 47 | cites it |
| 2022-06-16 | [Driver’s mobile phone usage detection using guided learning based on attention features and prior knowledge](https://doi.org/10.1016/j.eswa.2022.117877) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Tao Huang, Rui Fu, Qinyu Sun | 8 | cites it |
| 2025-05-27 | [A comprehensive review of on-board action recognition models in public transportation systems](https://doi.org/10.1016/j.eswa.2025.128311) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Cyril Meurie, Olivier Lézoray | 7 | cites it |
| 2022-10-27 | [Cell phone usage detection in roadway images: from plate recognition to violation classification](https://doi.org/10.1007/s00521-022-07943-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Amal Balabid, Areej Altaban, Maram Albsisi et al. | 2 | cites it |
| 2025-03-10 | [Optimal feature tuning model by variants of convolutional neural network with LSTM for driver distract detection in IoT platform](https://doi.org/10.1007/s10115-025-02342-4) | [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | Hameed Mutlag Farhan, Ayça Kurnaz Türkben, Raghda Awad Shaban Naseri | 2 | 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). state-farm-distracted-driver-detection: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-state-farm-distracted-driver-detection

```bibtex
@misc{scholar4ai-code-kaggle-competition-state-farm-distracted-driver-detection,
  author = {{Scholar4AI}},
  title = {state-farm-distracted-driver-detection: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-competition-state-farm-distracted-driver-detection}},
  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/).