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In an effort to catalog insect biodiversity, we propose a new large dataset of hand-labelled insect images, the BIOSCAN-Insect Dataset. Each record is taxonomically classified by an expert, and also has associated genetic information…

Insect-pests significantly impact global agricultural productivity and quality. Effective management involves identifying the full insect community, including beneficial insects and harmful pests, to develop and implement integrated pest…

Automatic recognition of insect sound could help us understand changing biodiversity trends around the world -- but insect sounds are challenging to recognize even for deep learning. We present a new dataset comprised of 26399 audio files,…

Sound · Computer Science 2025-03-20 Marius Faiß , Burooj Ghani , Dan Stowell

Biodiversity monitoring is crucial for tracking and counteracting adverse trends in population fluctuations. However, automatic recognition systems are rarely applied so far, and experts evaluate the generated data masses manually.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-31 Dimitri Korsch , Paul Bodesheim , Joachim Denzler

Wildlife monitoring is crucial to nature conservation and has been done by manual observations from motion-triggered camera traps deployed in the field. Widespread adoption of such in-situ sensors has resulted in unprecedented data volumes…

Computer Vision and Pattern Recognition · Computer Science 2020-09-25 Sayali Kulkarni , Tomer Gadot , Chen Luo , Tanya Birch , Eric Fegraus

Insects comprise millions of species, many experiencing severe population declines under environmental and habitat changes. High-throughput approaches are crucial for accelerating our understanding of insect diversity, with DNA barcoding…

Insect pests recognition is necessary for crop protection in many areas of the world. In this paper we propose an automatic classifier based on the fusion between saliency methods and convolutional neural networks. Saliency methods are…

Computer Vision and Pattern Recognition · Computer Science 2020-10-01 Loris Nanni , Gianluca Maguolo , Fabio Pancino

Fine-grained classification is challenging due to the difficulty of finding discriminatory features. This problem is exacerbated when applied to identifying species within the same taxonomical class. This is because species are often…

Computer Vision and Pattern Recognition · Computer Science 2023-07-24 Rita Pucci , Vincent J. Kalkman , Dan Stowell

Automated species identification and delimitation is challenging, particularly in rare and thus often scarcely sampled species, which do not allow sufficient discrimination of infraspecific versus interspecific variation. Typical problems…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Morris Klasen , Dirk Ahrens , Jonas Eberle , Volker Steinhage

Preserving the number and diversity of insects is one of our society's most important goals in the area of environmental sustainability. A prerequisite for this is a systematic and up-scaled monitoring in order to detect correlations and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Danja Brandt , Martin Tschaikner , Teodor Chiaburu , Henning Schmidt , Ilona Schrimpf , Alexandra Stadel , Ingeborg E. Beckers , Frank Haußer

Insects are a crucial part of our ecosystem. Sadly, in the past few decades, their numbers have worryingly decreased. In an attempt to gain a better understanding of this process and monitor the insects populations, Deep Learning may offer…

Artificial Intelligence · Computer Science 2022-06-16 Teodor Chiaburu , Felix Biessmann , Frank Hausser

Global biodiversity is declining at an unprecedented rate, yet little information is known about most species and how their populations are changing. Indeed, some 90% of Earth's species are estimated to be completely unknown. Machine…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Yuyan Chen , Nico Lang , B. Christian Schmidt , Aditya Jain , Yves Basset , Sara Beery , Maxim Larrivée , David Rolnick

In entomology and ecology research, biologists often need to collect a large number of insects, among which beetles are the most common species. A common practice for biologists to organize beetles is to place them on trays and take a…

Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and…

The BIOSCAN project, led by the International Barcode of Life Consortium, seeks to study changes in biodiversity on a global scale. One component of the project is focused on studying the species interaction and dynamics of all insects. In…

Computer Vision and Pattern Recognition · Computer Science 2022-11-07 Nicholas Pellegrino , Zahra Gharaee , Paul Fieguth

Entomologists, ecologists and others struggle to rapidly and accurately identify the species of bumble bees they encounter in their field work and research. The current process requires the bees to be mounted, then physically shipped to a…

Computer Vision and Pattern Recognition · Computer Science 2020-06-23 Venkat Margapuri , George Lavezzi , Robert Stewart , Dan Wagner

With fine-grained classification, we identify unique characteristics to distinguish among classes of the same super-class. We are focusing on species recognition in Insecta, as they are critical for biodiversity monitoring and at the base…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Rita Pucci , Vincent J. Kalkman , Dan Stowell

The rapid global loss of biodiversity, particularly among insects, represents an urgent ecological crisis. Current methods for insect species discovery are manual, slow, and severely constrained by taxonomic expertise, hindering timely…

Ground beetles are a highly sensitive and speciose biological indicator, making them vital for monitoring biodiversity. However, they are currently an underutilized resource due to the manual effort required by taxonomic experts to perform…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 S M Rayeed , Alyson East , Samuel Stevens , Sydne Record , Charles V Stewart

Existing image classification datasets used in computer vision tend to have a uniform distribution of images across object categories. In contrast, the natural world is heavily imbalanced, as some species are more abundant and easier to…

Computer Vision and Pattern Recognition · Computer Science 2018-04-12 Grant Van Horn , Oisin Mac Aodha , Yang Song , Yin Cui , Chen Sun , Alex Shepard , Hartwig Adam , Pietro Perona , Serge Belongie
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