Comparative Analysis of Recurrent vs. Temporal Convolutional Autoencoders for Detecting Container Impacts During Quay Crane Handling

Comparative Analysis of Recurrent vs. Temporal Convolutional Autoencoders for Detecting Container Impacts During Quay Crane Handling

This research develops and validates a novel impact detection system for container monitoring using autoencoders embedded within an edge computing unit. This solution addresses common limitations in current container tracking systems, such as a lack of real-time processing and reliance on cloud conn...

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Bibliographic Details
Main Authors: Sergej Jakovlev, Tomas Eglynas, Edvinas Pocevicius, Miroslav Voznak, Gediminas Gricius, Valdas Jankunas, Mindaugas Jusis
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Journal of Marine Science and Engineering
Subjects:
autoencoder
impact detection
accelerator
Online Access:https://www.mdpi.com/2077-1312/13/7/1231
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