Skip to content

Projects

Research systems, and things built for the joy of building them.

2 entries

0 / 2 explored on this device

A sea-themed 3D portfolio starter and portable design skill. Explore a procedural world by boat, reveal an illustrative wave field, and build a personal theme with readable content and documented asset sources.

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.

Figure detail

Open original ↗
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.

AI-assisted illustration authored for this website. See Kim & Oikonomou, UZH (2024), for the original report.

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