Towards real-time monitoring of insect species populations
Name
s41598-024-68502-8.pdf
Description
Published version
Size
1.87 MB
Format
Adobe PDF
Checksum (MD5)
ac3f77eb0f3cc3bf5055d2c7257cf349
Author(s)
Venverloo, Titus
Duarte, Fábio
Date Issued
2024
Journal
Scientific Reports
Publisher
Springer Science and Business Media LLC
Citation
Venverloo, T., Duarte, F. Towards real-time monitoring of insect species populations. Sci Rep 14, 18727 (2024).
Version
Final published version
Abstract
Insect biodiversity and abundance are in global decline, potentially leading to a crisis with profound ecological and economic consequences. Methods and technologies to monitor insect species to aid in preservation efforts are rapidly being developed yet their adoption has been slow and focused on specific use cases. We propose a computer vision model that works towards multi-objective insect species identification in real-time and on a large scale. We leverage an image data source with 16 million instances and a recent improvement in the YOLO computer vision architecture to present a quick and open-access method to develop visual AI models to monitor insect species across climatic regions.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs
Persistent DSpace Link
DOI of Published Version
10.1038/s41598-024-68502-8
