A comprehensive survey on test-time adaptation under distribution shifts
Abstract Machine learning methods strive to acquire a robust model during the training
process that can effectively generalize to test samples, even in the presence of distribution …
process that can effectively generalize to test samples, even in the presence of distribution …
Deep learning as a tool for ecology and evolution
Deep learning is driving recent advances behind many everyday technologies, including
speech and image recognition, natural language processing and autonomous driving. It is …
speech and image recognition, natural language processing and autonomous driving. It is …
Overview of lifeclef 2024: Challenges on species distribution prediction and identification
Biodiversity monitoring using machine learning and AI-based approaches is becoming
increasingly popular. It allows for providing detailed information on species distribution and …
increasingly popular. It allows for providing detailed information on species distribution and …
Visualization and classification of mushroom species with multi-feature fusion of metaheuristics-based convolutional neural network model
Determining the correct mushroom species with the necessary ecological characteristics is
critical to continue mushroom production, which is essential in gastronomy. The mushroom …
critical to continue mushroom production, which is essential in gastronomy. The mushroom …
Learning plant biodiversity in nature: The use of the citizen–science platform iNaturalist as a collaborative tool in secondary education
Biodiversity is a concept of great scientific interest and social value studied in different
subjects of the secondary education curriculum. Citizen–science programs may contribute to …
subjects of the secondary education curriculum. Citizen–science programs may contribute to …
Overview of lifeclef 2023: evaluation of ai models for the identification and prediction of birds, plants, snakes and fungi
Biodiversity monitoring through AI approaches is essential, as it enables the efficient
analysis of vast amounts of data, providing comprehensive insights into species distribution …
analysis of vast amounts of data, providing comprehensive insights into species distribution …
Danish fungi 2020-not just another image recognition dataset
We introduce a novel fine-grained dataset and benchmark, the Danish Fungi 2020 (DF20).
The dataset, constructed from observations submitted to the Atlas of Danish Fungi, is unique …
The dataset, constructed from observations submitted to the Atlas of Danish Fungi, is unique …
Overview of FungiCLEF 2024: Revisiting fungi species recognition beyond 0-1 cost
The third edition of the fungi recognition challenge, FungiCLEF 2024, organized within
LifeCLEF, advances the field of mushroom species identification using computer vision and …
LifeCLEF, advances the field of mushroom species identification using computer vision and …
Species determination using AI machine-learning algorithms: Hebeloma as a case study
P Bartlett, U Eberhardt, N Schütz, HJ Beker - IMA fungus, 2022 - Springer
The genus Hebeloma is renowned as difficult when it comes to species determination.
Historically, many dichotomous keys have been published and used with varying success …
Historically, many dichotomous keys have been published and used with varying success …
Automatic fungi recognition: deep learning meets mycology
The article presents an AI-based fungi species recognition system for a citizen-science
community. The system's real-time identification too—FungiVision—with a mobile …
community. The system's real-time identification too—FungiVision—with a mobile …