Design and Architecture for Signal and Image Processing

19th International Workshop, DASIP 2026, Krakow, Poland, January 26 - 28, 2026, Proceedings
Erscheinungsjahr 2026
ISBN: 978-3-032-23870-2
Verlag: Springer

Buch, Englisch, 197 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Computer Science

This book constitutes the refereed conference proceedings of the 19th International Workshop on Design and Architecture for Signal and Image Processing, DASIP 2026, held in Krakow, Poland, during January 2026.

The 15 full papers included in this book were carefully reviewed and selected from 30 submissions. They were organized in topical sections as follows: Reconfigurable Computing and Design Tools; AI Accelerators, Architectures and Benchmarking; and Secure and Dependable Embedded Systems.

Zielgruppe

Research

Autoren/Hrsg.

Kowalczyk, Marcin

Monière, Camille

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik

Inhaltsverzeichnis

.- Reconfigurable Computing and Design Tools .

.- A Framework for Automated Integration of High-Level Simulators in RISC-V SoCs.

.- An Open-Source Framework Bridging System-Level Measurements and Circuit-Level Energy Consumption and Latency Characteristics.

.- MultiGRA: Expanding the CGRA Design Space with a Mixed- Granularity Approach.

.- Resource-Guided FPGA Floorplanning via Quad-Tree-Based NLP Optimization.

.- Sigma Delta DACs for Low Latency High Sampling Rate Audio on an FPGA.

.- AI Accelerators, Architectures and Benchmarking .

.- Automated Design of CNN-based Image Classifiers for Hailo-8L Accelerator.

.- Benchmarking Deep Learning Convolutions on Energy-constrained CPUs.

.- C3M-ViT: A Configurable Matrix Multiplication Module for Energy-Efficient Vision Transformer Accelerator.

.- Comparative Benchmark of Scaled-YOLOv4 on Graphcore IPU and NVIDIA GPU.

.- FPGA-Based Anomaly Detection for Medical IoT: Trade-Offs between hls4ml and FINN.

.- Training for Mixed-Precision Integer Weights, Activations and Embeddings in BERT.

.- Secure and Dependable Embedded Systems .

.- ARMOR : Accelerator Runtime Monitoring and cOntrolled identity enfoRcement.

.- BERT-Inspired HT Localization on FPGA AI Accelerators.

.- Fault Injection Attacks in On-Chip Interconnects: A Comparative Study of Wishbone, AXI-Lite, and AXI.

.- UAVLnQ: An Architecture for Security Analysis of Cyber-Physical Network Behavior in UAV Swarms.