Principles of Catastrophic Forgetting for Continual Semantic Segmentation in Automated Driving

Deep learning excels at extracting complex patterns but faces catastrophic forgetting when fine-tuned on new data. This book investigates how class- and domain-incremental learning affect neural networks for automated driving, identifying semantic shifts and feature changes as key factors. Tools for...

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Detalles Bibliográficos

Autor Principal:	Kalb, Tobias Michael
Formato:	Online
Idioma:	inglés
Publicado:	KIT Scientific Publishing 2024
Subjects:	Automated Driving; Semantic Segmentation; Catastrophic Forgetting; Continual Learning; Deep Learning; Automatisiertes Fahren; Semantische Segmentierung; Katastrophales Vergessen; Kontinuierliches Lernen thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
Acceso en liña:	https://library.oapen.org/handle/20.500.12657/94140
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