40 citations · 43 across the 8 of their papers we have counts for
5 papers · 1 filter
MALPOLON: A Framework for Deep Species Distribution Modeling
Theo Larcher, Lukas Picek, Benjamin Deneu +3
This paper describes a deep-SDM framework, MALPOLON. Written in Python and built upon the PyTorch library, this framework aims to facilitate training and inferences of deep species…
WildFusion: Individual Animal Identification with Calibrated Similarity Fusion
Vojtěch Cermak, Lukas Picek, Lukáš Adam +2
We propose a new method - WildFusion - for individual identification of a broad range of animal species. The method fuses deep scores (e.g., MegaDescriptor or DINOv2) and local mat…
Animal Identification with Independent Foreground and Background Modeling
Lukas Picek, Lukas Neumann, Jiri Matas
We propose a method that robustly exploits background and foreground in visual identification of individual animals. Experiments show that their automatic separation, made easy wit…
GeoPlant: Spatial Plant Species Prediction Dataset
Lukas Picek, Christophe Botella, Maximilien Servajean +7
The difficulty of monitoring biodiversity at fine scales and over large areas limits ecological knowledge and conservation efforts. To fill this gap, Species Distribution Models (S…
FungiTastic: A multi-modal dataset and benchmark for image categorization
Lukas Picek, Klara Janouskova, Vojtech Cermak +1
We introduce a new, challenging benchmark and a dataset, FungiTastic, based on fungal records continuously collected over a twenty-year span. The dataset is labelled and curated by…