Search Results for author: Peter Naylor

Found 4 papers, 4 papers with code

Implicit neural representation for change detection

1 code implementation28 Jul 2023 Peter Naylor, Diego Di Carlo, Arianna Traviglia, Makoto Yamada, Marco Fiorucci

We outperform the previous methods by a margin of 10% in the intersection over union metric.

Change Detection

Optimal Transport for Change Detection on LiDAR Point Clouds

1 code implementation14 Feb 2023 Marco Fiorucci, Peter Naylor, Makoto Yamada

The method is based on unbalanced optimal transport and can be generalised to any change detection problem with LiDAR data.

Change Detection Multi-class Classification +1

Scale dependant layer for self-supervised nuclei encoding

1 code implementation22 Jul 2022 Peter Naylor, Yao-Hung Hubert Tsai, Marick Laé, Makoto Yamada

Recent developments in self-supervised learning give us the possibility to further reduce human intervention in multi-step pipelines where the focus evolves around particular objects of interest.

Self-Supervised Learning

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