Abalone Computer Vision Paper Accepted in Frontiers in AI
May 1, 2026·
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1 min read
Edwin Solares
Our paper “Deep Learning Classification of Reproductive Tissue from Ultrasound: Sex Determination in Red Abalone” has been accepted for publication in Frontiers in Artificial Intelligence.
This work demonstrates that convolutional neural networks can reliably classify biological reproductive tissue from ultrasound imagery, providing a non-invasive approach to sex determination in aquaculture species. The methodology reduces stress on animals and operational costs for producers.
Citation: Solares E et al. (2026) “Deep Learning Classification of Reproductive Tissue from Ultrasound: Sex Determination in Red Abalone.” Frontiers in AI 9:1794183. DOI: 10.3389/FRAI.2026.1794183
Authors
Edwin Solares
(he/him)
Lecturer in Computer Science & Data Science
I am a computational biologist and data scientist bridging artificial intelligence,
evolutionary genomics, and climate-resilient agriculture. My research leverages
cutting-edge machine learning and bioinformatics to address global food security
challenges in the face of rapid climate change. With publications in high-impact
journals including Nature Plants, PNAS, and Genome Research (h-index: 7), I develop
tools and methods that advance both computational science and real-world applications.