Artificial intelligence analysis for feed ratio optimization in precision aquaculture

• المؤلف الرئيسي: Galenius, Bryan Timothy
• مؤلفون آخرون: Ng Yin Kwee
• التنسيق: Final Year Project
• اللغة: English
• منشور في: Nanyang Technological University 2024
• الموضوعات: Computer and Information Science; Engineering; Aquaculture; Computer vision; Satiety; Machine learning; Hunger detection
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/176594
• المؤسسة: Nanyang Technological University

Aquaculture products’ increasing demand emphasizes the importance of FCR (Feed Conversion Ratio) optimization. While efforts to improve FCR of specific species exist, a universal method is lacking. Therefore, we present a hunger detection method generalized for different aquaculture species by...