no code implementations • 1 May 2024 • Sizhuo Li, Dimitri Gominski, Martin Brandt, Xiaoye Tong, Philippe Ciais
Image-level regression is an important task in Earth observation, where visual domain and label shifts are a core challenge hampering generalization.
no code implementations • 14 Nov 2023 • Dimitri Gominski, Ankit Kariryaa, Martin Brandt, Christian Igel, Sizhuo Li, Maurice Mugabowindekwe, Rasmus Fensholt
There is a rising interest in mapping trees using satellite or aerial imagery, but there is no standardized evaluation protocol for comparing and enhancing methods.
no code implementations • 19 Mar 2021 • Dimitri Gominski, Valérie Gouet-Brunet, Liming Chen
Pick a training dataset, pick a backbone network for feature extraction, and voil\`a ; this usually works for a variety of use cases.
no code implementations • 26 Feb 2021 • Dimitri Gominski, Valérie Gouet-Brunet, Liming Chen
Advances in high resolution remote sensing image analysis are currently hampered by the difficulty of gathering enough annotated data for training deep learning methods, giving rise to a variety of small datasets and associated dataset-specific methods.
no code implementations • 19 Sep 2019 • Dimitri Gominski, Martyna Poreba, Valérie Gouet-Brunet, Liming Chen
This article proposes to study the behavior of recent and efficient state-of-the-art deep-learning based image descriptors for content-based image retrieval, facing a panel of complex variations appearing in heterogeneous image datasets, in particular in cultural collections that may involve multi-source, multi-date and multi-view Permission to make digital