Water object detection is the process of identifying various objects either on the surface of the water or under water
through images or videos. The objects to be detected are like floats, marine species, ships, pipelines etc. In this article, an
extensive survey has been made on different strategies developed to detect and recognize underwater objects and objects on the
water surface. Various methods have been proposed by numerous scientists to detect water targets based on image processing,
neural networks, deep learning methods like faster R-CNN, YOLO, adaptive filtering schemes, background subtraction methods
etc. The analysed methods can be used in several areas including aquatic study, maintaining and fixing damages of underwater
structures.
