In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …

We have witnessed great interest and a wealth of promise in content-based image retrieval
as an emerging technology. While the last decade laid foundation to such promise, it also …

Objective measures of image quality generally operate by comparing pixels of a “degraded”
image to those of the original. Relative to human observers, these measures are overly …

Diffusion models have been shown to be capable of generating high-quality images,
suggesting that they could contain meaningful internal representations. Unfortunately, the …

In this work we propose a novel interpretation of residual networks showing that they can be
seen as a collection of many paths of differing length. Moreover, residual networks seem to …

Recognition algorithms based on convolutional networks (CNNs) typically use the output of
the last layer as feature representation. However, the information in this layer may be too …

Research in texture recognition often concentrates on the problem of material recognition in
uncluttered conditions, an assumption rarely met by applications. In this work we conduct a …

Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …

Patterns and textures are key characteristics of many natural objects: a shirt can be striped,
the wings of a butterfly can be veined, and the skin of an animal can be scaly. Aiming at …

Optical flow computation is a key component in many computer vision systems designed for
tasks such as action detection or activity recognition. However, despite several major …