Application of Machine Learning Techniques in Aquaculture
In this paper we present applications of different machine learning algorithms in aquaculture. Machine learning algorithms learn models from historical data. In aquaculture historical data are obtained from farm practices, yields, and environmental data sources. Associations between these different variables can be obtained by applying machine learning algorithms to historical data. In this paper we present applications of different machine learning algorithms in aquaculture applications.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningSimilar Papers 제목 키워드 기반
Fish Disease Detection Using Image Based Machine Learning Technique in Aquaculture
Fish diseases in aquaculture constitute a significant hazard to nutriment security. Identification of infected fishes in aquaculture remains challenging to find out at the early stage due to the dearth of necessary infra…
BIG-bench Machine LearningImage AugmentationImage ClassificationAQUA: A Large Language Model for Aquaculture & Fisheries
Aquaculture plays a vital role in global food security and coastal economies by providing sustainable protein sources. As the industry expands to meet rising demand, it faces growing challenges such as disease outbreaks,…
Decision Support Systems in Fisheries and Aquaculture: A systematic review
Decision support systems help decision makers make better decisions in the face of complex decision problems (e.g. investment or policy decisions). Fisheries and Aquaculture is a domain where decision makers face such de…
Fish feeding behavior recognition and intensity quantification methods in aquaculture: From single modality analysis to multimodality fusion
As a key part of aquaculture management, fish feeding behavior recognition and intensity quantification has been a hot area of great concern to researchers, and it plays a crucial role in monitoring fish health, guiding …
ManagementTiny Machine Learning for Real-Time Aquaculture Monitoring: A Case Study in Morocco
Aquaculture, the farming of aquatic organisms, is a rapidly growing industry facing challenges such as water quality fluctuations, disease outbreaks, and inefficient feed management. Traditional monitoring methods often …
Anomaly Detection