Name: Principles of Catastrophic Forgetting for Continual Semantic Segmentation in Automated Driving
Price: 42.5 CHF
Availability: InStock
ISBN: 9783731513735

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Zurich

Lausanne

Wohlen

Basel

Kriens

Winterthur

Bern

Dietikon

St. Gallen

Geneva

KIT Scientific Publishing

The book "Principles of Catastrophic Forgetting for Continual Semantic Segmentation in Automated Driving" provides a comprehensive examination of the challenges encountered when using deep learning in automated vehicle systems. In particular, it highlights the phenomenon of catastrophic forgetting, which occurs when neural networks are fine-tuned on new data. The author, Tobias Michael Kalb, analyzes how class- and domain-incremental learning affects the performance of neural networks and identifies semantic shifts and changes in features as critical factors. The book also offers tools for the quantitative measurement of forgetting and demonstrates how various strategies, such as image augmentation, pretraining, and architectural adjustments, can help mitigate catastrophic forgetting. These insights are especially relevant for professionals in the fields of technology and IT who are involved in the development and optimization of automated driving systems.

Actual product image Principles of Catastrophic Forgetting for Continual Semantic Segmentation in Automated Driving (English, Paperback, Tobias Michael Kalb)

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