Design and Architecture for Signal and Image Processing
portes grátis
Design and Architecture for Signal and Image Processing
18th International Workshop, DASIP 2025, Barcelona, Spain, January 20-22, 2025, Proceedings
Lorandel, Jordane; Kamaleldin, Ahmed
Springer International Publishing AG
04/2025
125
Mole
9783031878961
Pré-lançamento - envio 15 a 20 dias após a sua edição
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.- Specialized Hardware Architecture for Efficient Processing.
.- CSD-Driven Speedup in RISC-V Processor.
.- Efficient FPGA implementation of ViT Non-Linear Functions.
.- LiFT: Lightweight,FPGA-tailored 3D object detection based on LIDAR data.
.- Efficient Processing using AI for Image, Vision and Signal Applications.
.- A practical HW-Aware NAS flow for AI vision applications on embedded heterogeneous SoCs.
.- Endoscopy image classification for wireless cpasules with CNNs on microcontroller-based platforms.
.- Joint Underwater Depth Estimation and Dehazing from Single Image using Attention U-Net.
.- KD-AHOSVD: Neural Network Compression via Knowledge Distillation and Tensor Decomposition.
.- Analysis of Emerging Techniques for Signal Processing Applications.
.- Novel scheduling and shifter networks for 5G LDPC decoders.
.- Comparison Between In-core Hardware IDS, Off-core Hardware IDS and Software IDS.
.- Comparative Study of Memory Optimization Techniques for Dataflow-modeled Applications.
.- CSD-Driven Speedup in RISC-V Processor.
.- Efficient FPGA implementation of ViT Non-Linear Functions.
.- LiFT: Lightweight,FPGA-tailored 3D object detection based on LIDAR data.
.- Efficient Processing using AI for Image, Vision and Signal Applications.
.- A practical HW-Aware NAS flow for AI vision applications on embedded heterogeneous SoCs.
.- Endoscopy image classification for wireless cpasules with CNNs on microcontroller-based platforms.
.- Joint Underwater Depth Estimation and Dehazing from Single Image using Attention U-Net.
.- KD-AHOSVD: Neural Network Compression via Knowledge Distillation and Tensor Decomposition.
.- Analysis of Emerging Techniques for Signal Processing Applications.
.- Novel scheduling and shifter networks for 5G LDPC decoders.
.- Comparison Between In-core Hardware IDS, Off-core Hardware IDS and Software IDS.
.- Comparative Study of Memory Optimization Techniques for Dataflow-modeled Applications.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Architectures;Embedded and cyber-physical systems;real-time systems;parallel computing methodology;Artificial Intelligence;Machine Learning;Modeling and Simulation;Distributed computing methodology;Security in Hardware;theory and Algorithms for application domains;Design and analysis of algorithms;hardware test;Emerging technologies;Electronic Design Automation;Very Large Scale Integration Design;Communication hardware interfaces and storage;cross-computing tools and techniques;network components
.- Specialized Hardware Architecture for Efficient Processing.
.- CSD-Driven Speedup in RISC-V Processor.
.- Efficient FPGA implementation of ViT Non-Linear Functions.
.- LiFT: Lightweight,FPGA-tailored 3D object detection based on LIDAR data.
.- Efficient Processing using AI for Image, Vision and Signal Applications.
.- A practical HW-Aware NAS flow for AI vision applications on embedded heterogeneous SoCs.
.- Endoscopy image classification for wireless cpasules with CNNs on microcontroller-based platforms.
.- Joint Underwater Depth Estimation and Dehazing from Single Image using Attention U-Net.
.- KD-AHOSVD: Neural Network Compression via Knowledge Distillation and Tensor Decomposition.
.- Analysis of Emerging Techniques for Signal Processing Applications.
.- Novel scheduling and shifter networks for 5G LDPC decoders.
.- Comparison Between In-core Hardware IDS, Off-core Hardware IDS and Software IDS.
.- Comparative Study of Memory Optimization Techniques for Dataflow-modeled Applications.
.- CSD-Driven Speedup in RISC-V Processor.
.- Efficient FPGA implementation of ViT Non-Linear Functions.
.- LiFT: Lightweight,FPGA-tailored 3D object detection based on LIDAR data.
.- Efficient Processing using AI for Image, Vision and Signal Applications.
.- A practical HW-Aware NAS flow for AI vision applications on embedded heterogeneous SoCs.
.- Endoscopy image classification for wireless cpasules with CNNs on microcontroller-based platforms.
.- Joint Underwater Depth Estimation and Dehazing from Single Image using Attention U-Net.
.- KD-AHOSVD: Neural Network Compression via Knowledge Distillation and Tensor Decomposition.
.- Analysis of Emerging Techniques for Signal Processing Applications.
.- Novel scheduling and shifter networks for 5G LDPC decoders.
.- Comparison Between In-core Hardware IDS, Off-core Hardware IDS and Software IDS.
.- Comparative Study of Memory Optimization Techniques for Dataflow-modeled Applications.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Architectures;Embedded and cyber-physical systems;real-time systems;parallel computing methodology;Artificial Intelligence;Machine Learning;Modeling and Simulation;Distributed computing methodology;Security in Hardware;theory and Algorithms for application domains;Design and analysis of algorithms;hardware test;Emerging technologies;Electronic Design Automation;Very Large Scale Integration Design;Communication hardware interfaces and storage;cross-computing tools and techniques;network components
