Deep Learning Classification of Reproductive Tissue from Ultrasound: Sex Determination in Red Abalone

May 1, 2026·
Edwin Solares
Edwin Solares
,
et al.
· 1 min read
Abstract
This study develops deep learning classification models to determine the sex of Red Abalone (Haliotis rufescens) from ultrasound images of reproductive tissue, providing a non-invasive approach that reduces stress on animals and operational costs for producers.
Type
Publication
Frontiers in Artificial Intelligence
publications

This work demonstrates that convolutional neural networks can reliably classify biological reproductive tissue from ultrasound imagery, opening a pathway for non-invasive sex determination across aquaculture species.

Deep Learning Computer Vision Aquaculture Ultrasound Classification
Edwin Solares
Authors
Edwin Solares (he/him)
Executive Director, ESB AI Lab Corporation
Executive Director of ESB AI Lab Corporation, a 501(c)(3) nonprofit advancing research in AI, machine learning, computer vision, and genomics. Previously a Lecturer at UC San Diego. My research harnesses AI and bioinformatics for food security and species conservation. Published in Nature Plants, PNAS, Genome Research, and G3 (h-index: 7).
Authors
et al.