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] …

The aim of the research described in this article is to accelerate object detection in images
and video sequences using graphics processors. It includes algorithmic modifications and …

Bringing together experts in multimodal signal processing, this book provides a detailed
introduction to the area, with a focus on the analysis, recognition and interpretation of human …

In this paper, we introduce a novel architecture of an engine for high performance multi-
scale detection of objects in videos based on WaldBoost training algorithm. The key …

Usage of statistical classifiers, namely AdaBoost and its modifications, is very common in
object detection and pattern recognition. Performance of such classifiers strongly depends …

This paper introduces a novel method of wear debris analysis through classification of the
particles based on machine learning. Wear debris consists of particles of metal found in eg …

The wear debris of engineering equipment (such as combustion engines, gearboxes, etc.)
consists of metal particles which can be obtained from lubricants used in the equipment. The …

Object detection, or more generally pattern detection and recognition, can be based on
many different principles. The objects can be described through their structure, shape, color …

This dissertation contains studies on visual attention, as measured by gaze orientation, and
the use of mobile eye-tracking and pupillometry in applications. It combines the …

The thesis deals with image classifiers and their implementation using FPGA technology.
There are discussed weak and strong classifiers in the work. As an example of strong …