Underwater Visual Localization Using Machine Learning and LSTM: Introduction | HackerNoon
Briefly

Visual localization via cameras offers an accurate solution for underwater inspection near marine structures where acoustic navigation is hindered. Machine learning regression methods like PoseNet show promising precision in simulated underwater datasets.
This study delves into enhancing the accuracy of localization models using deeper neural networks and incorporating long-short-term memory (LSTM) to leverage spatial correlation in image features.
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