Project

2024

Cross-Dataset Human Activity Recognition

A UZH master’s project with Hyeongkyun Kim on self-supervised learning and enhanced fine-tuning for activity recognition across datasets.

Overview

Cross-domain activity recognition: self-supervised pretraining followed by enhanced fine-tuning with classical features, unknown samples and augmentation. — An illustration of learning and transferring activity representations.Source report ↗AI-assisted illustration authored for this website. See Kim & Oikonomou, UZH (2024), for the original report.

Cross-domain activity recognition: self-supervised pretraining followed by enhanced fine-tuning with classical features, unknown samples and augmentation. — An illustration of learning and transferring activity representations.Source report ↗AI-assisted illustration authored for this website. See Kim & Oikonomou, UZH (2024), for the original report.

Detail

A UZH master’s project with Hyeongkyun Kim on self-supervised learning and enhanced fine-tuning for activity recognition across datasets.

Role: Coauthor

Elsewhere

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