Gender Classification by Deep Learning on Millions of Weakly Labelled Images
By Sen Jia, Thomas Lansdall-Welfare, Nello Cristianini. 2016
48 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
Citations in the corpus
- Exposing and Correcting the Gender Bias in Image Captioning Datasets and Models (2019, methodology): “Gender classification in images - Gender classification from images is a popular task with several works in the literature, including [Jia et al., 2016], [Mansanet et al., 2016], [Antipov et al., 2016].”
- Right for the Right Reason: Training Agnostic Networks (2018, unknown): “using proxy signals that are expected to be somewhat correlated to the intended target concept [5], [11].”