Toward unbiased emotion recognition: overcoming user bias with siamese convolutional networks

• Published in: Signal, image and video processing Vol. 19; no. 11
• Main Authors: La Porta, Nicolò, Oldano, Gilles, Puiatti, Alessandro, Leidi, Tiziano, Papandrea, Michela
• Format: Journal Article
• Language: English
• Published: London Springer London 01.11.2025; Springer Nature B.V
• Subjects: Bias; Computer Imaging; Computer Science; Datasets; Emotion recognition; Emotions; Human bias; Image Processing and Computer Vision; Machine learning; Multimedia Information Systems; Original Paper; Pattern Recognition and Graphics; Physiology; Qualitative analysis; Representations; Signal,Image and Speech Processing; Vision; Siamese Networks; Biosignal Processing; User Bias; Emotion Recognition; Affective Computing

Purpose: Emotion Recognition (ER) systems are designed for an accurate inference of human emotions. Emotions are elicited by stimuli provided by the environment, such as social interactions or exposure to salient events, and are expressed by individuals in a strictly subjective manner. ER systems ar...