Image Blending in a High Frame Rate FPGA-based Multi-Camera System

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DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automata

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Current Dynamic Texture Synthesis (DyTS) models can synthesize realistic videos. However, they require a slow iterative optimization process to synthesize a single fixed-size short video, and they do not offer any post-training control over the synthesis p ...

Ieee Computer Soc2023

Two-level Data Augmentation for Calibrated Multi-view Detection

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Data augmentation has proven its usefulness to improve model generalization and performance. While it is commonly applied in computer vision application when it comes to multi-view systems, it is rarely used. Indeed geometric data augmentation can break th ...

IEEE COMPUTER SOC2023

Temperature Impact on Remote Power Side-Channel Attacks on Shared FPGAs

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To answer the growing demand for hardware acceleration, Amazon, Microsoft, and many other major cloud service providers have included field-programmable gate arrays (FPGAs) in their datacenters. However, researchers have shown that cloud FPGAs, when shared ...

IEEE2023

Assessment of the Bundle SNSPD Plus FPGA-Based TDC for High-Performance Time Measurements

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Counting single photons and measuring their arrival time is of crucial importance for imaging and quantum applications that use single photons to outperform classical techniques. The investigation of the coincidence, i.e. correlation, between photons can b ...

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DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

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Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...

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On the Maximum Power Density of Implanted Antennas within Simplified Body Phantoms

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With the application requirements of wireless technology in implantable bioelectronics, knowledge of the fundamental limits for implanted antennas becomes critical. In this work, we investigated the variation of maximum power density within simplified body ...

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Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

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Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

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Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

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reference data for "A Critical Comparison of Annual Glare Simulation Methods"

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Scene and reference results files for: "A Critical Comparison of Annual Glare Simulation Methods" Stephen Wasilewski, Jan Wienold, Marilyne Andersen 2022 Buildsim Nordic, Copenhagen Contents: 01-06*.tar.gz: reference simulation image archives, one ...

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On combining denoising with learning-based image decoding

Touradj Ebrahimi, Michela Testolina

Noise is an intrinsic part of any sensor and is present, in various degrees, in any content that has been captured in real life environments. In imaging applications, several pre- and post-processing solutions have been proposed to cope with noise in captu ...

SPIE2022

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