Computer vision and machine learning methods that utilize Convolutional Neural Networks and Long Short-Term Memory Networks for fish species identification, fish population density, and biomass estimation from underwater video sequences are described.
In this talk I will describe computer vision and machine learning methods that utilize Convolutional Neural Networks and Long Short-Term Memory Networks for fish species identification, fish population density, and biomass estimation from underwater video sequences, and present an integrated semi-automated fish visual census system for fish biodiversity monitoring of our seas.