Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformer

Shaif Chowdhury, Sadia Nasrin Tisha, Monica E. McGarrity, Greg Hamerly

Abstract: Aquatic species like zebra and quagga mussels are invasive in United States waterways and cause ecological and economic damage. Due to the time-consuming nature of conventional early detection methods, there is a need for automated systems to detect and classify invasive and non-invasive species using a video-based system without any human supervision. We present a video classification model for rapidly recognizing invasive and non-invasive mussel larvae from plankton or water sample videos.