Related papers: Hardware-irrelevant parallel processing system
The GRAPPA (GeneRalized Autocalibrating Partially Parallel Acquisitions) method of parallel MRI makes use of an autocalibration scan (ACS) to determine a set of synthesis coefficients to be used in the image reconstruction. For EPI time…
In every imaging or sensing application, the physical hardware creates constraints that must be overcome or they limit system performance. Techniques that leverage additional degrees of freedom can effectively extend performance beyond the…
High-Performance Computing (HPC) platforms enable scientific software to achieve breakthroughs in many research fields such as physics, biology, and chemistry, by employing Research Software Engineering (RSE) techniques. These include 1)…
Photoplethysmography (PPG) is an attractive method to acquire vital signs such as heart rate and blood oxygenation and is frequently used in clinical and at-home settings. Continuous operation of health monitoring devices demands a low…
Photonic methods of radio-frequency waveform generation and processing provide performance and flexibility over electronic methods due to the ultrawide bandwidth offered by the optical carriers. However, they suffer from lack of integration…
Nowadays, we are to find out solutions to huge computing problems very rapidly. It brings the idea of parallel computing in which several machines or processors work cooperatively for computational tasks. In the past decades, there are a…
We propose advancing photonic in-memory computing through three-dimensional photonic-electronic integrated circuits using phase-change materials (PCM) and AlGaAs-CMOS technology. These circuits offer high precision (greater than 12 bits),…
Parallel imaging is ubiquitous in MRI, enabling diverse applications such as ultra-high-resolution functional and quantitative imaging with greater temporal resolution or reduced scan times respectively. Successful unfolding is contingent…
Mixed-criticality systems, where multiple systems with varying criticality-levels share a single hardware platform, require isolation between tasks with different criticality-levels. Isolation can be achieved with software-based solutions…
Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources. Hence, researchers have been exploring different energy-efficient solutions such as near-sensor processing, in-sensor…
Partial wave analysis is a key technique in hadron spectroscopy. The use of unbinned likelihood fits on large statistics data samples and ever more complex physics models makes this analysis technique computationally very expensive.…
General requirements for radar digital signal processing are ionospheric distortion and Doppler dispersion correction, which has historically required radar-specific hardware to implement in real time. Although analog solutions are…
Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) systems are investigated under spatially correlated fading channels using realistic…
This book focuses on the use of algorithmic high-level synthesis (HLS) to build application-specific FPGA systems. Our goal is to give the reader an appreciation of the process of creating an optimized hardware design using HLS. Although…
High-throughput imaging workflows, such as Parallel Rapid Imaging with Spectroscopic Mapping (PRISM), generate data at rates that exceed conventional real-time processing capabilities. We present a scalable FPGA-based preprocessing pipeline…
Recent research on vision backbone architectures has predominantly focused on optimizing efficiency for hardware platforms with high parallel processing capabilities. This category increasingly includes embedded systems such as mobile…
Photonic computing chips have made significant progress in accelerating linear computations, but nonlinear computations are usually implemented in the digital domain, which introduces additional system latency and power consumption, and…
Panchromatic (PAN) and multi-spectral (MS) image fusion, named Pan-sharpening, refers to super-resolve the low-resolution (LR) multi-spectral (MS) images in the spatial domain to generate the expected high-resolution (HR) MS images,…
Significance: Histopathological analysis of tissues is an essential tool for grading, staging, diagnosing and resecting cancers and other malignancies. Current histopathological techniques require substantial sample processing prior to…
Remote sensing images inevitably suffer from various degradation factors during acquisition, including atmospheric interference, sensor limitations, and imaging conditions. These complex and heterogeneous degradations pose severe challenges…