sovrasov/flops-counter.pytorch: papers linking to it

GitHub · 2,984 stars · 307 forks · Python · license MIT · created 2018 · github.com/sovrasov/flops-counter.pytorch

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to sovrasov/flops-counter.pytorch (https://github.com/sovrasov/flops-counter.pytorch), 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#

7 papers in the tracked journals link to the GitHub repository sovrasov/flops-counter.pytorch in their Crossref records, the first in 2024; most of them (4) in 2025.
By category: AI (7); the journals with the most are Machine Learning (2), Neural Computing and Applications (2) and Expert Systems with Applications (1).

By year#

20242025

Papers linking to sovrasov/flops-counter.pytorch by publication year
Year	Papers
2024	3
2025	4

Journals#

Journals whose papers link to sovrasov/flops-counter.pytorch most
Journal	Papers
Machine Learning	2
Neural Computing and Applications	2
Expert Systems with Applications	1
Applied Intelligence	1
Cognitive Computation	1

Papers linking to sovrasov/flops-counter.pytorch, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-03-02	Yaru3DFPN: a lightweight modified 3D UNet with feature pyramid network and combine thresholding for brain tumor segmentation	Neural Computing and Applications	Agus Subhan Akbar, Chastine Fatichah, Nanik Suciati et al.	23	cites it
2024-05-27	Dual-Stream CoAtNet models for accurate breast ultrasound image segmentation	Neural Computing and Applications	Nadeem Zaidkilani, Miguel Ángel García, Domènec Puig	10	cites it
2024-04-01	Privacy-preserving visual analysis: training video obfuscation models without sensitive labels	Applied Intelligence	Sander De Coninck, Wei-Cheng Wang, Sam Leroux et al.	8	cites it
2025-02-20	Nettop: A light-weight network of orthogonal-plane features for image recognition	Machine Learning	Thanh Tuan Nguyen, Thanh Phương Nguyễn	4	cites it
2025-03-21	$$A^{2}$$DM: Enhancing EEG Artifact Removal by Fusing Artifact Representation into the Time-Frequency Domain	Cognitive Computation	Haoran Li, Fan Feng, Jiarong Kang et al.	4	cites it
2025-09-10	Composite human activity recognition utilizing knowledge distillation and sensor fusion focusing on resource constrained microcontrollers	Expert Systems with Applications	Athar Noor Mohammad Rafee, John Clear, Jannatun Noor	2	cites it
2025-03-25	Online dimensionality reduction through stacked generalization of spectral methods with deep networks	Machine Learning	Juan Carlos Alvarado‐Pérez, Miguel Ángel García, Domènec Puig	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). sovrasov/flops-counter.pytorch: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-sovrasov-flops-counter-pytorch

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

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