dfaker/df: papers linking to it

GitHub · 485 stars · 133 forks · Python · license MPL-2.0 · created 2018 · archived · github.com/dfaker/df

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to dfaker/df (https://github.com/dfaker/df), 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#

4 papers in the tracked journals link to the GitHub repository dfaker/df in their Crossref records, the first in 2021; most of them (1) in 2025.
By category: AI (3) and Information Systems (1); the journals with the most are Expert Systems with Applications (2), International Journal of Information Management Data Insights (1) and Neural Computing and Applications (1).
2 of the papers build on one another: a later paper cites an earlier one that also links dfaker/df.

By year#

20212025

Papers linking to dfaker/df by publication year
Year	Papers
2021	1
2022	1
2024	1
2025	1

Journals#

Journals whose papers link to dfaker/df most
Journal	Papers
Expert Systems with Applications	2
International Journal of Information Management Data Insights	1
Neural Computing and Applications	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Exposing deepfakes using a deep multilayer perceptron – convolutional neural network model International Journal of Information Management Data Insights, 2021
- Unmasking deepfakes: A systematic review of deepfake detection and generation techniques using artificial intelligence Expert Systems with Applications, 2024 — cites the paper above

Papers linking to dfaker/df, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-05-18	Unmasking deepfakes: A systematic review of deepfake detection and generation techniques using artificial intelligence	Expert Systems with Applications	Fakhar Abbas, Araz Taeihagh	116	cites it
2021-12-22	Exposing deepfakes using a deep multilayer perceptron – convolutional neural network model	International Journal of Information Management Data Insights	Santosh Kolagati, T. Chindrella Priyadharshini, V. Mary Anita Rajam	88	cites it
2022-08-02	An integrated spatiotemporal-based methodology for deepfake detection	Neural Computing and Applications	Aya Ismail, Marwa S. Elpeltagy, Mervat S. Zaki et al.	42	cites it
2025-06-14	FAME: a lightweight spatio-temporal network for model attribution of face-swap deepfakes	Expert Systems with Applications	Wasim Ahmad, Yan‐Tsung Peng, Yuan-Hao Chang	10	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). dfaker/df: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-dfaker-df

@misc{scholar4ai-code-github-dfaker-df,
  author = {{Scholar4AI}},
  title = {dfaker/df: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-dfaker-df}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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