Plankton Recognition

Plankton recognition uses computer vision to automatically identify and quantify different plankton species in aquatic ecosystems, aiding in environmental monitoring and ecological research. Current research focuses on improving the robustness of deep learning models, such as convolutional neural networks and vision transformers, to variations in imaging conditions and dataset biases, often employing techniques like domain adaptation and ensemble methods. This automated approach offers significant advantages over manual analysis by increasing efficiency and enabling large-scale studies of plankton populations, which are crucial indicators of environmental health and change. The development of robust and generalizable plankton recognition systems is essential for advancing our understanding of aquatic ecosystems.