From Nov 2023 to Oct 2026, 57 archived papers mentioned Facial expression (FER2013, AffectNet, RAF-DB) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jan 2025 (4).
No paper of the tracked journals mentioned Facial expression (FER2013, AffectNet, RAF-DB) in the last 30 days (2026-10-07 to 2026-11-05).
From 2017 to 2026 (so far), Facial expression (FER2013, AffectNet, RAF-DB) was mentioned in 76 papers in the tracked journals, most of them in AI (66), higher education and research (4) and information systems (2).
20 of them were published in 2025, against 1 in 2017.
Since 2023, the institutions with the most of these papers were Chinese Academy of Sciences (5), Institute of Automation (4) and University of Chinese Academy of Sciences (4).
The journals publishing most of them were Neural Computing and Applications (9), Information Fusion (5) and Pattern Recognition (4).
The most-cited of them is “A comprehensive review of model compression techniques in machine learning” (Applied Intelligence, 2024), with 271 citations.
Papers use Facial expression (FER2013, AffectNet, RAF-DB) most often with ImageNet (23), Face recognition (LFW, CelebA, VGGFace2) (10) and Speech emotion (IEMOCAP, RAVDESS) (9); it has 12 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.
Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.
Papers use Facial expression (FER2013, AffectNet, RAF-DB) most often with ImageNet (23), Face recognition (LFW, CelebA, VGGFace2) (10) and Speech emotion (IEMOCAP, RAVDESS) (9); it has 12 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST. The whole network →
What papers use Facial expression (FER2013, AffectNet, RAF-DB) together with (at least 3 papers; lift 1 = chance)
Scholar4AI. (2026). Facial expression (FER2013, AffectNet, RAF-DB). Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/facial-expression-fer2013-affectnet-raf-db
@misc{scholar4ai-datasets-facial-expression-fer2013-affectnet-raf-db,
author = {{Scholar4AI}},
title = {Facial expression (FER2013, AffectNet, RAF-DB)},
year = {2026},
howpublished = {\url{https://scholar4ai.com/datasets/facial-expression-fer2013-affectnet-raf-db}},
urldate = {2026-11-05},
note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).