Fast animal detection in UAV images using convolutional neural networks. - Benjamin Kellenberger; Michele Volpi; Devis Tuia (IGARSS, 2017)

Learning class- and location-specific priors for urban semantic labeling with CNNs. - Benjamin Kellenberger; Michele Volpi; Devis Tuia (JURSE, 2017)

Learning Deep Structured Active Contours End-to-End. - Diego Marcos; Devis Tuia; Benjamin Kellenberger; Lisa Zhang; Min Bai; Renjie Liao; Raquel Urtasun (CVPR, 2018)

DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation. - Bharath Bhushan Damodaran; Benjamin Kellenberger; Rémi Flamary; Devis Tuia; Nicolas Courty (ECCV (4), 2018)

Detecting Animals in Repeated UAV Image Acquisitions by Matching CNN Activations with Optimal Transport. - Benjamin Kellenberger; Diego Marcos; Nicolas Courty; Devis Tuia (IGARSS, 2018)

A Deep Network Approach to Multitemporal Cloud Detection. - Devis Tuia; Benjamin Kellenberger; Adrián Pérez-Suay; Gustau Camps-Valls (IGARSS, 2018)

Best Practices to Train Deep Models on Imbalanced Datasets - A Case Study on Animal Detection in Aerial Imagery. - Benjamin Kellenberger; Diego Marcos; Devis Tuia (ECML/PKDD (3), 2018)

Land cover mapping at very high resolution with rotation equivariant CNNs: towards small yet accurate models. - Diego Marcos; Michele Volpi; Benjamin Kellenberger; Devis Tuia (CoRR, 2018)

Detecting Mammals in UAV Images: Best Practices to address a substantially Imbalanced Dataset with Deep Learning. - Benjamin Kellenberger; Diego Marcos; Devis Tuia (CoRR, 2018)

Scale equivariance in CNNs with vector fields. - Diego Marcos; Benjamin Kellenberger; Sylvain Lobry; Devis Tuia (CoRR, 2018)

When a Few Clicks Make All the Difference: Improving Weakly-Supervised Wildlife Detection in UAV Images. - Benjamin Kellenberger; Diego Marcos; Devis Tuia (CVPR Workshops, 2019)

Half a Percent of Labels is Enough: Efficient Animal Detection in UAV Imagery Using Deep CNNs and Active Learning. - Benjamin Kellenberger; Diego Marcos; Sylvain Lobry; Devis Tuia (IEEE Trans. Geosci. Remote. Sens., 2019)

Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images. - Xiaochen Zheng; Benjamin Kellenberger; Rui Gong; Irena Hajnsek; Devis Tuia (ICCVW, 2021)

How to find a good image-text embedding for remote sensing visual question answering? - Christel Chappuis; Sylvain Lobry; Benjamin Kellenberger; Bertrand Le Saux; Devis Tuia (MACLEAN@PKDD/ECML, 2021)

Mapping Vulnerable Populations with AI. - Benjamin Kellenberger; John E. Vargas-Muñoz; Devis Tuia; Rodrigo Caye Daudt; Konrad Schindler; Thao T.-T. Whelan; Brenda Ayo; Ferda Ofli; Muhammad Imran 002 (CoRR, 2021)

Seeing biodiversity: perspectives in machine learning for wildlife conservation. - Devis Tuia; Benjamin Kellenberger; Sara Beery; Blair R. Costelloe; Silvia Zuffi; Benjamin Risse; Alexander Mathis; Mackenzie W. Mathis; Frank van Langevelde; Tilo Burghardt; Roland Kays; Holger Klinck; et al. (CoRR, 2021)

Block Label Swap for Species Distribution Modelling. - Benjamin Kellenberger; Devis Tuia (CLEF (Working Notes), 2022)

Training Techniques for Presence-Only Habitat Suitability Mapping with Deep Learning. - Benjamin Kellenberger; Elijah Cole; Diego Marcos; Devis Tuia (IGARSS, 2022)

Fine-grained Population Mapping from Coarse Census Counts and Open Geodata. - Nando Metzger; John E. Vargas-Muñoz; Rodrigo Caye Daudt; Benjamin Kellenberger; Thao Ton-That Whelan; Ferda Ofli; Muhammad Imran 002; Konrad Schindler; Devis Tuia (CoRR, 2022)

LifeCLEF 2023 Teaser: Species Identification and Prediction Challenges. - Alexis Joly; Hervé Goëau; Stefan Kahl; Lukás Picek; Christophe Botella; Diego Marcos; Milan Sulc; Marek Hrúz; Titouan Lorieul; Sara Si-Moussi; Maximilien Servajean; Benjamin Kellenberger; et al. (ECIR (3), 2023)

Teaching Computer Vision for Ecology. - Elijah Cole; Suzanne Stathatos; Björn Lütjens; Tarun Sharma; Justin Kay; Jason R. Parham; Benjamin Kellenberger; Sara Beery (CoRR, 2023)

Datasets for "Where the White Continent is blue: deep learning locates bare ice in Antarctica". - Veronica Tollenaar; Harry Zekollari; Frank Pattyn; Marc Rußwurm; Benjamin Kellenberger; Stef Lhermitte; Maaike Izeboud; Devis Tuia (Zenodo, 2023)

POLO - Point-Based, Multi-class Animal Detection. - Giacomo May; Emanuele Dalsasso; Benjamin Kellenberger; Devis Tuia (ECCV Workshops (2), 2024)

Multi-scale and Multimodal Species Distribution Modeling. - Nina Van Tiel; Robin Zbinden; Emanuele Dalsasso; Benjamin Kellenberger; Loïc Pellissier; Devis Tuia (ECCV Workshops (2), 2024)

MaskSDM: Adaptive Species Distribution Modeling Through Data Masking. - Robin Zbinden; Nina Van Tiel; Gencer Sumbul; Benjamin Kellenberger; Devis Tuia (ECCV Workshops (2), 2024)

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning. - Robin Zbinden; Nina Van Tiel; Benjamin Kellenberger; Lloyd Hughes; Devis Tuia (Ecol. Informatics, 2024)

Datasets for "Where the White Continent is blue: deep learning locates bare ice in Antarctica". - Veronica Tollenaar; Harry Zekollari; Frank Pattyn; Marc Rußwurm; Benjamin Kellenberger; Stef Lhermitte; Maaike Izeboud; Devis Tuia (Zenodo, 2024)

Code for "Where the White Continent is blue: deep learning locates bare ice in Antarctica". - Veronica Tollenaar; Harry Zekollari; Frank Pattyn; Marc Rußwurm; Benjamin Kellenberger; Stef Lhermitte; Maaike Izeboud; Devis Tuia (Zenodo, 2024)

How to minimize the annotation effort in aerial wildlife surveys. - Giacomo May; Emanuele Dalsasso; Alexandre Delplanque; Benjamin Kellenberger; Devis Tuia (Ecol. Informatics, 2025)

MaskSDM with Shapley values to improve flexibility, robustness, and explainability in species distribution modeling. - Robin Zbinden; Nina Van Tiel; Gencer Sumbul; Chiara Vanalli; Benjamin Kellenberger; Devis Tuia (CoRR, 2025)