Sustainability, Год журнала: 2025, Номер 17(11), С. 5084 - 5084

Опубликована: Июнь 1, 2025

With the rising global demand for aquatic products, aquaculture has become a cornerstone of food security and sustainability. This review comprehensively analyzes application deep learning in sustainable aquaculture, covering key areas such as fish detection counting, growth prediction health monitoring, intelligent feeding systems, water quality forecasting, behavioral stress analysis. The study discusses suitability architectures, including CNNs, RNNs, GANs, Transformers, MobileNet, under complex environments characterized by poor image severe occlusion. It highlights ongoing challenges related to data scarcity, real-time performance, model generalization, cross-domain adaptability. Looking forward, paper outlines future research directions multimodal fusion, edge computing, lightweight design, synthetic generation, digital twin-based virtual farming platforms. Deep is poised drive toward greater intelligence, efficiency,

Язык: Английский