---
title: "z36jf: papers citing this dataset"
description: "5 papers in the tracked journals link to the OSF dataset z36jf in their Crossref records, the first in 2022; most of them (3) in 2023."
url: https://scholar4ai.com/code/osf-z36jf
markdown_url: https://scholar4ai.com/code/osf-z36jf.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 OSF dataset z36jf in their Crossref records, the first in 2022; most of them (3) in 2023. (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)
---

# z36jf: papers linking to it

Research papers in the 480 tracked journals that link to z36jf (https://osf.io/z36jf/), 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/z36jf/

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

## Key findings

- 5 papers in the tracked journals link to the OSF dataset z36jf in their Crossref records, the first in 2022; most of them (3) in 2023.
- By category: AI (5); the journals with the most are Neural Computing and Applications (5).
- 4 of the papers build on one another: a later paper cites an earlier one that also links z36jf.

## By year

*Papers linking to z36jf by publication year*

| Year | Papers |
|---|---:|
| 2022 | 1 |
| 2023 | 3 |
| 2026 | 1 |

## Journals

*Journals whose papers link to z36jf most*

| Journal | Papers |
|---|---:|
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 5 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Robust thermal infrared tracking via an adaptively multi-feature fusion model](https://doi.org/10.1007/s00521-022-07867-1) (Neural Computing and Applications, 2022)
  - [Repformer: a robust shared-encoder dual-pipeline transformer for visual tracking](https://doi.org/10.1007/s00521-023-08824-2) (Neural Computing and Applications, 2023) — cites the paper above
  - [Multiple frequency–spatial network for RGBT tracking in the presence of motion blur](https://doi.org/10.1007/s00521-023-09024-8) (Neural Computing and Applications, 2023) — cites the paper above
  - [GTAN: graph-based tracklet association network for multi-object tracking](https://doi.org/10.1007/s00521-023-09287-1) (Neural Computing and Applications, 2023) — cites the paper above

## Papers

*Papers linking to z36jf, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-10-12 | [Robust thermal infrared tracking via an adaptively multi-feature fusion model](https://doi.org/10.1007/s00521-022-07867-1) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Di Yuan, Xiu Shu, Qiao Liu et al. | 55 | cites it |
| 2023-07-22 | [Repformer: a robust shared-encoder dual-pipeline transformer for visual tracking](https://doi.org/10.1007/s00521-023-08824-2) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Fengwei Gu, Jun Lu, Chengtao Cai et al. | 16 | cites it |
| 2023-12-15 | [GTAN: graph-based tracklet association network for multi-object tracking](https://doi.org/10.1007/s00521-023-09287-1) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Jianfeng Lv, Yu Zhongliang, Yifan Liu et al. | 10 | cites it |
| 2023-10-03 | [Multiple frequency–spatial network for RGBT tracking in the presence of motion blur](https://doi.org/10.1007/s00521-023-09024-8) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Shenghua Fan, Xi Chen, Chu He et al. | 5 | cites it |
| 2026-02-01 | [Leveraging contrastive learning for cross-modal(X-modal) person identification](https://doi.org/10.1007/s00521-025-11693-6) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Unse Fatima, Zafran Khan, Piotr Indyk et al. | 1 | 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). z36jf: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/osf-z36jf

```bibtex
@misc{scholar4ai-code-osf-z36jf,
  author = {{Scholar4AI}},
  title = {z36jf: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/osf-z36jf}},
  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/).