Underwater Dock Detection through Convolutional Neural Networks Trained with Artificial Image Generation

Author:

Chavez-Galaviz Jalil1,Mahmoudian Nina1

Affiliation:

1. School of Mechanical Engineering, Purdue University,West Lafayette,IN,USA,47907

Funder

ONR

Publisher

IEEE

Reference19 articles.

1. Marine Organism Detection and Classification from Underwater Vision Based on the Deep CNN Method

2. Underwater image enhancement with encoding-decoding deep CNN networks

3. Uwgan: underwater gan for real-world underwater color restoration and dehazing;wang;ArXiv Preprint,2019

4. Docking Control of an Autonomous Underwater Vehicle Using Reinforcement Learning

5. Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?;johnson-roberson;ArXiv Preprint,2016

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1. Underwater image processing based on CNN applications: A review;Proceedings of the Cognitive Models and Artificial Intelligence Conference;2024-05-25

2. Review of underwater visual navigation and docking: advances and challenges;Sixth Conference on Frontiers in Optical Imaging and Technology: Imaging Detection and Target Recognition;2024-04-30

3. Autonomous Navigation of Robots: Optimization with DQN;Applied Sciences;2023-06-16

4. Terminal Homing Work for Auv Based on New Structured Cnn and Homing Strategy;2023

5. Efficient Underwater Docking Detection using Knowledge Distillation and Artificial Image Generation;2022 IEEE/OES Autonomous Underwater Vehicles Symposium (AUV);2022-09-19

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