Jan 23, 2019 · This work explores joint classification of gender, age and race. Specifically, we here propose a Multi-Task Convolution Neural Network (MTCNN) employing joint ...
This work explores joint classification of gender, age and race. Specifically, we here propose a Multi-Task Convolution Neural Network (MTCNN) employing ...
This work explores joint classification of gender, age and race. Specifically, we here propose a Multi-Task Convolution Neural Network (MTCNN) employing joint ...
A Multi-Task Convolution Neural Network (MTCNN) employing joint dynamic loss weight adjustment towards classification of named soft biometrics, ...
Oct 2, 2018 · This work explores the joint classification of gender, age and race. Specifically, we here propose a Multi-Task Convolution Neural Network ...
This work explores joint classification of gender, age and race. Specifically, we here propose a Multi-Task Convolution Neural Network (MTCNN) employing ...
In this paper, we propose a novel bias mitigation technique that leverages the power of semantic preserving augmentations at the image- and feature-level.
Other Mitigation Methods. Mitigating Bias in Gender, Age and Ethnicity Classification: a Multi-Task Convolution Neural Network Approach · InclusiveFaceNet ...
Mitigating Bias in Gender, Age and Ethnicity Classification: a Multi-Task Convolution Neural Network Approach. Abhijit Das,. Antitza Dantcheva,. Francois ...
People also ask
How to reduce bias in NLP models?
What is bias in convolutional neural network?
In this paper, we propose a solution for real-time user profiling based on a multi-task convolutional neural network (CNN) for gender, age, ethnicity and ...
Missing: Mitigating | Show results with:Mitigating