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10/21/2022
Virtual Triggering: a Technique to Segment Cryptographic Processes in Side Channel Traces
Side-Channel Attacks (SCAs) exploit data correla-tion in signals leaked ...
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03/01/2021
Run-time Performance Monitoring of Heterogenous Hw/Sw Platforms Using PAPI
In the era of Cyber Physical Systems, designers need to offer support fo...
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02/02/2021
Why is FPGA-GPU Heterogeneity the Best Option for Embedded Deep Neural Networks?
Graphics Processing Units (GPUs) are currently the dominating programmab...
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12/15/2020
Gegelati: Lightweight Artificial Intelligence through Generic and Evolvable Tangled Program Graphs
Tangled Program Graph (TPG) is a reinforcement learning technique based ...
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05/06/2020
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
This paper reviews the Challenge on Image Demoireing that was part of th...
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02/18/2020
NoiseBreaker: Gradual Image Denoising Guided by Noise Analysis
Fully supervised deep-learning based denoisers are currently the most pe...
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10/18/2019
OpenDenoising: an Extensible Benchmark for Building Comparative Studies of Image Denoisers
Image denoising has recently taken a leap forward due to machine learnin...
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10/16/2019
Electro-Magnetic Side-Channel Attack Through Learned Denoising and Classification
This paper proposes an upgraded electro-magnetic side-channel attack tha...
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06/30/2018
The Challenge of Multi-Operand Adders in CNNs on FPGAs: How not to solve it!
Convolutional Neural Networks (CNNs) are computationally intensive algor...
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05/26/2018
Accelerating CNN inference on FPGAs: A Survey
Convolutional Neural Networks (CNNs) are currently adopted to solve an e...
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11/20/2017
Tactics to Directly Map CNN graphs on Embedded FPGAs
Deep Convolutional Neural Networks (CNNs) are the state-of-the-art in im...
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05/04/2017
Hardware Automated Dataflow Deployment of CNNs
Deep Convolutional Neural Networks (CNNs) are the state of the art syste...
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03/21/2017