On-board classification of underwater images using hybrid classical-quantum CNN based method

arXiv:2404.13130v1 Announce Type: new
Abstract: Underwater images taken from autonomous underwater vehicles (AUV's) often suffer from low light, high turbidity, poor contrast, motion-blur and excessive light scattering and hence require image enhancement techniques for object recognition. Machine learning methods are being increasingly used for object recognition under such adverse conditions. These enhanced object recognition methods of images taken from AUV's has potential applications in underwater pipeline and optical fibre surveillance, ocean bed resource extraction, ocean floor mapping, underwater species exploration, …

abstract arxiv autonomous board classification cnn contrast cs.cv hybrid image images light low machine machine learning object quant-ph quantum recognition type underwater vehicles