Convolutional neural networks (CNN) is a specialized case of artificial neural networks
(ANN) and finds its application in computer vision and parallel distributed computing for …

We review the current state of research in endoscopic optical coherence tomography (OCT).
We first survey the range of available endoscopic optical imaging techniques. We then …

We propose a novel approach to learn and recognize natural scene categories. Unlike
previous work, it does not require experts to annotate the training set. We represent the …

Design for Embedded Image Processing on FPGAs Bridge the gap between software and
hardware with this foundational design reference Field-programmable gate arrays (FPGAs) …

Terahertz imaging and spectroscopy is an exciting technology that has the potential to
provide insights in medical imaging. Prior research has leveraged statistical inference to …

Learning which stimuli (classical conditioning) or which actions (operant conditioning)
predict rewards or punishments can improve chances of survival. However, the circuit …

This work proposes the use of an unmanned aerial vehicle (UAV) with an autopilot to identify
the defects present in municipal sewerage pipes. The framework also includes an effective …

Convolution is an important mathematical tool in both fields of signal and image processing.
It is employed in filtering [1, 2], denoising [3], edge detection [4, 5], correlation [6] …

Illegal migration as well as wildfires constitute commonplace situations in southern
European countries, where the mountainous terrain and thick forests make the surveillance …

The built-in stress test (BIST) is extensively used for diagnostics or identification of failure.
The current version of BIST approach is focused on reactive failure detection and provides …