Verfahren und System zur Identifizierung und Abschwächung von Verzerrung Beim Trainieren von Tiefenlernmodellen

Details

Veröffentlichungs-Nr.

EP4303769

Aktenzeichen

EP23179266

Anmeldetag

14. Juni 2023

Veröffentlichung

6. August 2025

Erteilung

6. August 2025

Rechtsraum

EP

IPC

G06N3/0455G06N3/084G06V10/82G06V10/764G06V10/77G06V10/774G06V10/776

Abstract

This disclosure relates generally to identification and mitigation of bias while training deep learning models. Conventional methods do not provide effective methods for bias identification, and they require pre-defined concepts and rules for bias mitigation. The embodiments of the present disclosure train an auto-encoder to produce a generalized representation of an input image by decomposing into a set of latent embedding. The set of latent embedding are used to learn the shape and color concepts of the input image. The feature specialization is done by training an auto-encoder to reconstruct the input image using the shape embedding modulated by color embedding. To identify the bias, permutation invariant neural network is trained for classification task and attribution scores corresponding to each concept embedding are computed. The method also performs de-biasing the classifier by training it with a set of counterfactual images generated by modifying the latent embedding learned by the auto-encoder.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete