UKDM: Underwater keypoint detection and matching using underwater image enhancement techniques
This work addresses the challenge of robust keypoint detection and matching in underwater environments, which is incremental as it applies existing deep learning models to this specific domain.
The paper tackled the problem of underwater keypoint detection and matching by applying underwater image enhancement techniques, resulting in significant improvements over traditional methods on various datasets.
The purpose of this paper is to explore the use of underwater image enhancement techniques to improve keypoint detection and matching. By applying advanced deep learning models, including generative adversarial networks and convolutional neural networks, we aim to find the best method which improves the accuracy of keypoint detection and the robustness of matching algorithms. We evaluate the performance of these techniques on various underwater datasets, demonstrating significant improvements over traditional methods.