This paper presents a comprehensive review of fish feeding behavior analysis in aquaculture, focusing on its tasks, techniques, and applications. It distinguishes core subtasks, summarizes behavioral characteristics and evaluation metrics, and examines the development of computer vision, acoustics, sensors, and multimodal fusion technologies. The review also discusses challenges and future research directions for intelligent feeding and sustainable aquaculture management. AI
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IMPACT Provides a foundational review for applying AI and computer vision techniques to improve efficiency and sustainability in aquaculture.
RANK_REASON This is a research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.7]