Crypto-and-Lobesia-segmentation

Zenodo (CERN European Organization for Nuclear Research) 2026 Open access

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Authors: Massimo De Agro', Livia De Fazi, Valeria Zeni, Fabio Marino, Renato Ricciardi
DOI: 10.5281/zenodo.18984888
Cited by: 0

Abstract

Code, trained YOLO11 segmentation model and annotated dataset for the automatic detection and counting of Lobesia botrana and Cryptoblabes gnidiella males on the sticky bottoms of pheromone traps, distinguishing them from non-target insects.

Fields of Study & Subjects

Smart Agriculture and AI Advanced Neural Network Applications Insect behavior and control techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 March 2026
Language
EN