[Paper Review] Optimized Deep Learning Models for AUV Seabed Image Analysis

Rajesh Sharma R, Akey Sungheetha+1 more|arXiv (Cornell University)|Nov 17, 2023

Underwater Acoustics Research12 citations

TL;DR

This paper provides a detailed summary and comparison of the latest advancements in AUV seabed image processing using optimized deep learning models.

ABSTRACT

Using autonomous underwater vehicles, or AUVs, has completely changed how we gather data from the ocean floor. AUV innovation has advanced significantly, especially in the analysis of images, due to the increasing need for accurate and efficient seafloor mapping. This blog post provides a detailed summary and comparison of the most current advancements in AUV seafloor image processing. We will go into the realm of undersea technology, covering everything through computer and algorithmic advancements to advances in sensors and cameras. After reading this page through to the end, you will have a solid understanding of the most up-to-date techniques and tools for using AUVs to process seabed photos and how they could further our comprehension of the ocean floor

Motivation & Objective

• Motivate improved accuracy and efficiency in seabed mapping using AUVs.
• Review and compare current deep learning-based seabed image processing techniques.
• Discuss algorithmic, sensor, and camera advancements enabling better AUV vision.

Proposed method

• Provide a detailed summary and comparison of the most current advancements in AUV seafloor image processing.
• Discuss computer vision and algorithmic advances relevant to seabed analysis.
• Cover advances in sensors and cameras used by AUVs to support image analysis.

Experimental results

Research questions

• RQ1 What are the most up-to-date deep learning techniques for AUV seabed image analysis?
• RQ2 How do these techniques address accuracy and efficiency in seafloor mapping with AUVs?
• RQ3 What are the key challenges and gaps in current AUV seabed image processing methods?

Key findings

• The paper offers a detailed summary and comparison of the latest advancements in AUV seabed image processing.
• It covers a broad scope from computer vision and algorithmic developments to sensor and camera improvements.
• The work emphasizes the integration of undersea technology with image analysis techniques.