Challenging Deep Image Descriptors for Retrieval in Heterogeneous Iconographic Collections. - Dimitri Gominski; Martyna Poreba; Valérie Gouet-Brunet; Liming Chen 002 (SUMAC @ ACM Multimedia, 2019)

Connecting Images through Time and Sources: Introducing Low-data, Heterogeneous Instance Retrieval. - Dimitri Gominski; Valérie Gouet-Brunet; Liming Chen 002 (CoRR, 2021)

Connecting Images through Sources: Exploring Low-Data, Heterogeneous Instance Retrieval. - Dimitri Gominski; Valérie Gouet-Brunet; Liming Chen 002 (Remote. Sens., 2021)

Generalizable features and image search for multi-source interconnection and analysis. (Description et recherche d'image généralisables pour l'interconnexion et l'analyse multi-source). - Dimitri Gominski (2021)

Cross-dataset Learning for Generalizable Land Use Scene Classification. - Dimitri Gominski; Valérie Gouet-Brunet; Liming Chen 002 (CVPR Workshops, 2022)

Benchmarking Individual Tree Mapping with Sub-meter Imagery. - Dimitri Gominski; Ankit Kariryaa; Martin Brandt; Christian Igel; Sizhuo Li; Maurice Mugabowindekwe; Rasmus Fensholt (CoRR, 2023)

Mining Field Data for Tree Species Recognition at Scale. - Dimitri Gominski; Daniel Ortiz-Gonzalo; Martin Brandt; Maurice Mugabowindekwe; Rasmus Fensholt (ECCV Workshops (2), 2024)

Get Your Embedding Space in Order: Domain-Adaptive Regression for Forest Monitoring. - Sizhuo Li; Dimitri Gominski; Martin Brandt; Xiaoye Tong; Philippe Ciais (ECCV (77), 2024)

Mapping forest-agroforest frontiers in the Peruvian Amazon with deep learning and PlanetScope satellite data. - Wanting Yang; Daniel Ortiz-Gonzalo; Xiaoye Tong; Dimitri Gominski; Rasmus Fensholt (Ecol. Informatics, 2025)

An Operational Framework to Track Individual Farmland Trees Over Time at National Scales Using PlanetScope. - Florian Reiner; Dimitri Gominski; Rasmus Fensholt; Martin Brandt (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)