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Showing 11 of 11 academic articles

Comparing an FPGA to a Cell for an Image Processing Application

Robert W. Ives, Randy P. Broussard, Hau Ngo, Ryan N. Rakvic • EURASIP Journal on Advances in Signal Processing (2010)

Modern advancements in configurable hardware, most notably Field-Programmable Gate Arrays (FPGAs), have provided an exciting opportunity to discover the parallel nature of modern image processing algorithms. On the other hand, PlayStation3 ...

DOAJ Open Access (DOAJ) DOI: 10.1155/2010/764838

FPGA-based multi-view stereo system with flexible measurement setup

Christina Junger, Richard Fütterer, Maik Rosenberger, Gunther Notni • Measurement: Sensors (2022)

In recent years, stereoscopic image processing algorithms have gained importance for a variety of applications. To capture larger measurement volumes, multiple stereo systems are combined into a multi-view stereo (MVS) system. To reduce the...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.measen.2022.100425

Very large‐scale integration architecture for video stabilisation and implementation on a field programmable gate array‐based autonomous vehicle

Tahiyah Nou‐Shene, Vikramkumar Pudi, K. Sridharan, Vineetha Thomas et al. • IET Computer Vision (2015)

Autonomous vehicles engaged in terrain exploration are typically equipped with a camera. The camera is subjected to vibration as the vehicle moves so that the videos captured require stabilisation to facilitate accurate interpretation by re...

DOAJ Open Access (DOAJ) DOI: 10.1049/iet-cvi.2014.0120

A Wilson–Cowan reservoir computer for interpretable spatiotemporal vision

Sharmarke A. Gabayre, Sergey Savel’ev, Varuna De Silva, Mindula Illeperuma et al. • Scientific Reports (2026)

Abstract We present a Wilson–Cowan reservoir computer (WC–RC) that treats a retinotopic excitatory–inhibitory neural field as a structured reservoir. Travelling waves and bounded oscillations provide an interpretable spatiotemporal basis, w...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-49359-5

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access (2020)

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3039858

A Multi-Class ECG Signal Classifier Using a Binarized Depthwise Separable CNN with the Merged Convolution–Pooling Method

Rui Zhang, Ranran Zhou, Zuting Zhong, Haifeng Qi et al. • Sensors (2024)

Binarized convolutional neural networks (bCNNs) are favored for the design of low-storage, low-power cardiac arrhythmia classifiers owing to their high weight compression rate. However, multi-class classification of ECG signals based on bCN...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24227207

Trinity: In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics

Ji-Hoon Kim, Seunghee Han, Kwanghyun Park, Soo-Young Ji et al. • IEEE Access (2024)

The ability to perform machine learning (ML) tasks in a database management system (DBMS) is a new paradigm for conventional database systems as it enables advanced data analytics on top of well-established capabilities of DBMSs. However, t...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3347725