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Beschreibung
This book constitutes the refereed proceedings of the 17th International Workshop on Design and Architecture for Signal and Image Processing, DASIP 2024, held in Munich, Germany, during January 17-19, 2024.

The 9 full papers presented in this book were carefully reviewed and selected from 21 submissions. The workshop provided an inspiring international forum for the latest innovations and developments in the fields of leading signal, image, and video processing and machine learning in custom embedded, edge, and cloud computing architectures and systems.
This book constitutes the refereed proceedings of the 17th International Workshop on Design and Architecture for Signal and Image Processing, DASIP 2024, held in Munich, Germany, during January 17-19, 2024.

The 9 full papers presented in this book were carefully reviewed and selected from 21 submissions. The workshop provided an inspiring international forum for the latest innovations and developments in the fields of leading signal, image, and video processing and machine learning in custom embedded, edge, and cloud computing architectures and systems.
Inhaltsverzeichnis

.- Specialized Hardware Architectures for Signal and Image Processing.

.- A Highly Configurable Platform for Advanced PPG Analysis.

.- sEMG-based Gesture Recognition with Spiking Neural Networks on Low-power FPGA.

.- Scalable FPGA Implementation of Dynamic Programming for Optimal Control of Hybrid Electrical Vehicles.

.- Optimization Approaches for Efficient Deployment of Signal and Image Processing Applications.

.- Wordlength Optimization for Custom Floating-point Systems.

.- An Initial Framework for Prototyping Radio-Interferometric Imaging Pipelines.

.- Scratchy: A Class of Adaptable Architectures with Software-Managed Communication For Edge Streaming Applications.

.- Digital Signal Processing Design for Reconfigurable Systems.

.- Standalone Nested Loop Acceleration on CGRAs for Signal Processing Applications.

.- Improving the Energy Efficiency of CNN Inference on FPGA using Partial Reconfiguration.

.- Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-based Vision.

Details
Erscheinungsjahr: 2024
Fachbereich: Nachrichtentechnik
Genre: Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Reihe: Lecture Notes in Computer Science
Inhalt: xvi
123 S.
9 s/w Illustr.
39 farbige Illustr.
123 p. 48 illus.
39 illus. in color.
ISBN-13: 9783031628733
ISBN-10: 303162873X
Sprache: Englisch
Einband: Kartoniert / Broschiert
Redaktion: Dias, Tiago
Busia, Paola
Herausgeber: Tiago Dias/Paola Busia
Hersteller: Springer
Springer International Publishing AG
Lecture Notes in Computer Science
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 8 mm
Von/Mit: Tiago Dias (u. a.)
Erscheinungsdatum: 17.07.2024
Gewicht: 0,224 kg
Artikel-ID: 129292184

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