Deep Learning Architecture based Multi Class Coral Reef Image Classification

Deep learning techniques have abundant possibilities on how it can be used on a certain set of topics. One such topic we chose to use deep learning architecture to classify is the coral reef. Underwater resources like coral reefs are abundant. It is important to keep a track on coral reefs as it has a lot of benefits for the environment. As a result, there is a growing need for effective methods of monitoring and protecting these valuable ecosystems. One promising approach for addressing this need is the use of deep learning models for coral reef image classification and detection. We use YOLOv5 and its models classify the different types of coral reefs that are present under the water. Different classes of coral reefs are also detected using YOLOv5 algorithm and all the models of YOLOv5 are compared with each other.