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We are losing biodiversity at an unprecedented scale and in many cases, we do not even know the basic data for the species. Traditional methods for wildlife monitoring are inadequate. Development of new computer vision tools enables the use…

Machine Learning · Computer Science 2019-08-08 Matteo Foglio , Lorenzo Semeria , Guido Muscioni , Riccardo Pressiani , Tanya Berger-Wolf

Many ecological questions center on complex phenomena, such as species interactions, behaviors, phenology, and responses to disturbance, that are inherently difficult to observe and sparsely documented. Community science platforms such as…

Forests play a crucial role in Earth's system processes and provide a suite of social and economic ecosystem services, but are significantly impacted by human activities, leading to a pronounced disruption of the equilibrium within…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Arthur Ouaknine , Teja Kattenborn , Etienne Laliberté , David Rolnick

In recent decades the set of knowledge, tools and practices, collectively referred to as "artificial intelligence" (AI), have become a mainstay of scientific research. Artificial intelligence techniques have not only developed enormously…

Physics and Society · Physics 2022-12-26 Floriana Gargiulo , Sylvain Fontaine , Michel Dubois , Paola Tubaro

Plot images are essential for ecological studies, enabling standardized sampling, biodiversity assessment, long-term monitoring and remote, large-scale surveys. Plot images are typically fifty centimetres or one square meter in size, and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Herve Goeau , Vincent Espitalier , Pierre Bonnet , Alexis Joly

Bird strikes present a huge risk for aircraft, especially since traditional airport bird surveillance is mainly dependent on inefficient human observation. Computer vision based technology has been proposed to automatically detect birds,…

Computer Vision and Pattern Recognition · Computer Science 2016-01-19 Ying Huang , Hong Zheng , Haibin Ling , Erik Blasch , Hao Yang

Deep learning (DL) algorithms are the state of the art in automated classification of wildlife camera trap images. The challenge is that the ecologist cannot know in advance how many images per species they need to collect for model…

Computer Vision and Pattern Recognition · Computer Science 2020-10-19 Saleh Shahinfar , Paul Meek , Greg Falzon

The Amazon rain forest is a vital ecosystem that plays a crucial role in regulating the Earth's climate and providing habitat for countless species. Deforestation in the Amazon is a major concern as it has a significant impact on global…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Nathalie Neptune , Josiane Mothe

Camera traps are a proven tool in biology and specifically biodiversity research. However, camera traps including depth estimation are not widely deployed, despite providing valuable context about the scene and facilitating the automation…

Computer Vision and Pattern Recognition · Computer Science 2021-02-11 Timm Haucke , Volker Steinhage

Wildlife trafficking remains a critical global issue, significantly impacting biodiversity, ecological stability, and public health. Despite efforts to combat this illicit trade, the rise of e-commerce platforms has made it easier to sell…

Plant diseases pose significant threats to agriculture. It necessitates proper diagnosis and effective treatment to safeguard crop yields. To automate the diagnosis process, image segmentation is usually adopted for precisely identifying…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Tianqi Wei , Zhi Chen , Xin Yu , Scott Chapman , Paul Melloy , Zi Huang

Large image collections generated from camera traps offer valuable insights into species richness, occupancy, and activity patterns, significantly aiding biodiversity monitoring. However, the manual processing of these datasets is…

We introduce and we analyze a new dataset which resembles the input to biological vision systems much more than most previously published ones. Our analysis leaded to several important conclusions. First, it is possible to disambiguate over…

Computer Vision and Pattern Recognition · Computer Science 2013-04-29 Alessandro Perina , Nebojsa Jojic

Plant species identification in the wild is a difficult problem in part due to the high variability of the input data, but also because of complications induced by the long-tail effects of the datasets distribution. Inspired by the most…

Computer Vision and Pattern Recognition · Computer Science 2021-06-07 Matthew R. Keaton , Ram J. Zaveri , Meghana Kovur , Cole Henderson , Donald A. Adjeroh , Gianfranco Doretto

Point counts (PCs) are widely used in biodiversity surveys, but despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability…

Datasets (semi-)automatically collected from the web can easily scale to millions of entries, but a dataset's usefulness is directly related to how clean and high-quality its examples are. In this paper, we describe and publicly release an…

Computer Vision and Pattern Recognition · Computer Science 2020-08-24 Houda Alberts , Iacer Calixto

Wildlife monitoring is crucial for studying biodiversity loss and climate change. Camera trap images provide a non-intrusive method for analyzing animal populations and identifying ecological patterns over time. However, manual analysis is…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Julian D. Santamaria , Claudia Isaza , Jhony H. Giraldo

Novel methods of analysis are needed to help advance our understanding of the intricate interplay between landscape changes, population dynamics, and sustainable development. Self organized machine learning has been highly successful in the…

Signal Processing · Electrical Eng. & Systems 2024-05-17 John M. Wandeto , Birgitta Dresp-Langley

Quadrat images are essential for ecological studies, as they enable standardized sampling, the assessment of plant biodiversity, long-term monitoring, and large-scale field campaigns. These images typically cover an area of fifty…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Giulio Martellucci , Herve Goeau , Pierre Bonnet , Fabrice Vinatier , Alexis Joly

With the advent of multispectral imagery and AI, there have been numerous works on automatic plant segmentation for purposes such as counting, picking, health monitoring, localized pesticide delivery, etc. In this paper, we tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Fabrice Mayran de Chamisso , Loïc Cotten , Valentine Dhers , Thomas Lompech , Florian Seywert , Arnaud Susset
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