Convolutional neural networks (CNNs) were inspired by early findings in the study of
biological vision. They have since become successful tools in computer vision and state-of …

One of the main challenges in machine vision relates to the problem of obtaining robust
representation of visual features that remain unaffected by geometric transformations. This …

Анотація The work is devoted to the study of pattern recognition features of industrial parts
in individual fasteners' forms. The main types of neural network architectures and their …

Convolutional Neural Networks (CNN) are a class of machine learning models
predominately used in computer vision tasks and can achieve human-like performance …

This paper explores the potential for performing temporal semantic segmentation in the
context of agricultural robotics without temporally labelled data. We achieve this by …

Studies in neuroscience inspired progress in the design of artificial neural networks (ANNs),
and, vice versa, ANNs provide new insights into the functioning of brain circuits. So far, the …

Studies in neuroscience inspired progress in the design of artificial neural networks (ANNs)
and vice versa ANNs have also started to provide new insights into the functioning of brain …