Machine learning tools represent key enablers for empowering material scientists and
engineers to accelerate the development of novel materials, processes and techniques. One …

Image segmentation is one of the most important tasks in medical image analysis and is
often the first and the most critical step in many clinical applications. In brain MRI analysis …

The capability of recognizing pedestrian attributes, such as gender and clothing style, at far
distance, is of practical interest in far-view surveillance scenarios where face and body close …

This paper reviewed major remote sensing image classification techniques, including pixel-
wise, sub-pixel-wise, and object-based image classification methods, and highlighted the …

This textbook on Photogrammetric Computer Vision–Statistics, Geometry, Orientation and
Reconstruction provides a statistical treatment of the geometry of multiple view analysis …

Decision forests (also known as random forests) are an indispensable tool for automatic
image analysis. This practical and easy-to-follow text explores the theoretical underpinnings …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

Networks and network analysis are arguably one of the largest growth areas of the early
twenty-first century in the quantitative sciences. Despite roots in social network analysis …

Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A
common constraint is that the labels should vary smoothly almost everywhere while …

The finite mixture (FM) model is the most commonly used model for statistical segmentation
of brain magnetic resonance (MR) images because of its simple mathematical form and the …