---
title: "s5d48: papers citing this dataset"
description: "4 papers in the tracked journals link to the OSF dataset s5d48 in their Crossref records, the first in 2022; most of them (2) in 2022."
url: https://scholar4ai.com/code/osf-s5d48
markdown_url: https://scholar4ai.com/code/osf-s5d48.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "4 papers in the tracked journals link to the OSF dataset s5d48 in their Crossref records, the first in 2022; most of them (2) in 2022. (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)
---

# s5d48: papers linking to it

Research papers in the 480 tracked journals that link to s5d48 (https://osf.io/s5d48/), 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.

- OSF
- https://osf.io/s5d48/

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

## Key findings

- 4 papers in the tracked journals link to the OSF dataset s5d48 in their Crossref records, the first in 2022; most of them (2) in 2022.
- By category: AI (4); the journals with the most are Expert Systems with Applications (1), International Journal of Computer Vision (1) and Journal Of Big Data (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links s5d48.

## By year

*Papers linking to s5d48 by publication year*

| Year | Papers |
|---|---:|
| 2022 | 2 |
| 2023 | 1 |
| 2025 | 1 |

## Journals

*Journals whose papers link to s5d48 most*

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 1 |
| [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | 1 |
| [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 1 |
| [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [DSRD-Net: Dual-stream residual dense network for semantic segmentation of instruments in robot-assisted surgery](https://doi.org/10.1016/j.eswa.2022.117420) (Expert Systems with Applications, 2022)
  - [A lightweight hierarchical feature fusion network for surgical instrument segmentation in internet of medical things](https://doi.org/10.1016/j.inffus.2025.103303) (Information Fusion, 2025) — cites the paper above

## Papers

*Papers linking to s5d48, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-04-27 | [DSRD-Net: Dual-stream residual dense network for semantic segmentation of instruments in robot-assisted surgery](https://doi.org/10.1016/j.eswa.2022.117420) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Tahir Mahmood, Se Woon Cho, Kang Ryoung Park | 39 | cites it |
| 2022-07-12 | [Surgical Tool Datasets for Machine Learning Research: A Survey](https://doi.org/10.1007/s11263-022-01640-6) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Mark Rodrigues, Michael Mayo, Panos Patros | 32 | cites it |
| 2023-05-25 | [DLA-E: a deep learning accelerator for endoscopic images classification](https://doi.org/10.1186/s40537-023-00775-8) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Hamidreza Bolhasani, Somayyeh Jafarali Jassbi, Arash Sharifi | 9 | cites it |
| 2025-05-09 | [A lightweight hierarchical feature fusion network for surgical instrument segmentation in internet of medical things](https://doi.org/10.1016/j.inffus.2025.103303) | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | Tahir Mahmood, Ganbayar Batchuluun, Seung Gu Kim et al. | 9 | 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). s5d48: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/osf-s5d48

```bibtex
@misc{scholar4ai-code-osf-s5d48,
  author = {{Scholar4AI}},
  title = {s5d48: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/osf-s5d48}},
  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/).