The number of fatal crashes on United States roadways has declined substantially since 2002, yet the number of fatalities involving two-wheeled motorists has consistently[...]

Deep neural networks (DNN) are proved to be effective and improve the performance dramatically in various kinds of computer vision tasks. The end-to-end learning manner i[...]

In this dissertation, we aim to investigate the problem of large-scale and fine-grained image recognition, which focuses on the differentiation of subtle differences amon[...]

Enabling computers to recognize objects present in images has been a long standing but tremendously challenging problem in the field of computer vision for decades. Beyon[...]

Automated human activity analysis for multi-camera networks requires algorithms that are both accurate and efficient for practical, real-time use. Current approaches face[...]

The goal of this experimental study is to examine the influence of performance recognitions that target either the team or the individual on subsequent productivity, enti[...]

The estimation and reconstruction of 3D architectural structures is of great interest in computer vision, as well as cultural heritage. This dissertation proposes a novel[...]

Beliefs about the existence and attractiveness of opportunities underpin entrepreneurial action. Belief formation is broken into two distinct phases. Third-person opportu[...]

Picking and placing parts is a fundamental operation involved in circuit board manufacturing and assembly plants. Pin thru-hole (PTH) components with non-standard feature[...]

Text analytics represent a set of scalable techniques that mine unstructured and semi-structured textual resources in order to extract useful knowledge for performing a t[...]