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A lot of work has been done to reach the best possible performance of predictive models on images. There are fewer studies about the resilience of these models when they are trained on image datasets that suffer modifications altering their…
Compartmentalization effectively prevents initial corruption from turning into a successful attack. This paper presents O2C, a pioneering system designed to enforce OS kernel compartmentalization on the fly. It not only provides immediate…
Compression of hyperspectral images onboard of spacecrafts is a tradeoff between the limited computational resources and the ever-growing spatial and spectral resolution of the optical instruments. As such, it requires low-complexity…
CBM (Compressed Baryonic Matter) is mainly used to study QCD phase diagram of strong interactions in high and moderate temperature region. Before the next generation GBTx based CBM DAQ system is built up, the DPB (Data Processing Board)…
Real-world applications are now processing big-data sets, often bottlenecked by the data movement between the compute units and the main memory. Near-memory computing (NMC), a modern data-centric computational paradigm, can alleviate these…
In this work we show how we can build a technology platform for cognitive imaging sensors using recent advances in recurrent neural network architectures and training methods inspired from biology. We demonstrate learning and processing…
X-ray computed tomography at the nanometer scale (nano-CT) offers a wide range of applications in scientific and industrial areas. Here we describe a reliable, user-friendly and fast software package based on LabVIEW that may allow to…
Many recent papers have demonstrated fast in-network computation using programmable switches, running many orders of magnitude faster than CPUs. The main limitation of writing software for switches is the constrained programming model and…
With the rapid development of connecting massive devices to the Internet, especially for remote areas without cellular network infrastructures, space-air-ground integrated networks (SAGINs) emerge and offload computation-intensive tasks. In…
This paper describes the development of a cost-effective yet precise indoor robot navigation system composed of a custom robot controller board and an indoor positioning system. First, the proposed robot controller board has been specially…
Autonomous-mobile cyber-physical machines are part of our future. Specifically, unmanned-aerial-vehicles have seen a resurgence in activity with use-cases such as package delivery. These systems face many challenges such as their…
In this thesis, we propose to tackle this important issue by designing and realizing a novel nano-optical device based on the use of a photonic crystal (PC) structure to generate an efficient coupling between the external source and a NA.…
Spiking neural networks (SNNs) implemented on neuromorphic processors (NPs) can enhance the energy efficiency of deployments of artificial intelligence (AI) for specific workloads. As such, NP represents an interesting opportunity for…
Ecological sciences are using imagery from a variety of sources to monitor and survey populations and ecosystems. Very High Resolution (VHR) satellite imagery provide an effective dataset for large scale surveys. Convolutional Neural…
This paper presents the development of a real time tracking algorithm that runs on a 1.2 GHz PC/104 computer on-board a small UAV. The algorithm uses zero mean normalized cross correlation to detect and locate an object in the image. A…
Error correction is essential for modern computing systems, enabling information to be processed accurately even in the presence of noise. Here, we demonstrate a new approach which exploits an error correcting phase that emerges in a system…
Earth observation (EO) missions traditionally rely on transmitting raw or minimally processed imagery from satellites to ground stations for computationally intensive analysis. This paradigm is infeasible for CubeSat systems due to…
Ambient backscatter communication (AmBC) enables radio-frequency (RF) powered backscatter devices (BDs) (e.g., sensors, tags) to modulate their information bits over ambient RF carriers in an over-the-air manner. This technology also called…
This paper investigates the intelligent computing task-oriented computing offloading and semantic compression in mobile edge computing (MEC) systems. With the popularity of intelligent applications in various industries, terminals…
Modern satellites deployed in low Earth orbit (LEO) accommodate processing payloads that can be exploited for edge computing. Furthermore, by implementing inter-satellite links, the LEO satellites in a constellation can route the data…