Advancing Underwater Vision: A Survey of Deep Learning Models for Underwater Object Recognition and Tracking

Underwater computer vision plays a vital role in ocean research, enabling autonomous navigation, infrastructure inspections, and marine life monitoring. However, the underwater environment presents unique challenges, including color distortion, limited visibility, and dynamic light conditions, which hinder the performance of traditional image processing methods. Recent advancements in deep learning (DL) have demonstrated remarkable success in overcoming these challenges by enabling robust feature extraction, image enhancement, and object recognition. This review provides a comprehensive analysis of cutting-edge deep learning architectures designed for underwater object detection, segmentation, and tracking.…

• CU
  Changsha University of Science and Technology

  Awards: 8434000534, CIRA-2021-085, RC1-2018-KUCARS