Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Engineering
Integrated Compressive Sensing And Feature Descriptors- A Framework For Facial Recognition Systems, Ali Kadhem Jaber
Integrated Compressive Sensing And Feature Descriptors- A Framework For Facial Recognition Systems, Ali Kadhem Jaber
Dissertations
Facial recognition is still a challenge in many applications, particularly in surveillance, security systems, and human-computer interactive (HCI) tools. The impact of real-world environmental variations on the performance of any facial recognition system can be significant. These variations may include illumination, facial expressions, poses, disguises (facial hair, glasses or cosmetics) and partial face occlusion. Furthermore, the number of images (samples) needed for facial recognition systems can be very large, much larger than what is typically required by an algorithm, and this is often made worse with expansion of the feature space dimensionality. Truly, the “curse of dimensionality” haunts any real-time …
Signal Processing For Microwave Imaging Systems With Very Sparse Array, Xiahan Yang
Signal Processing For Microwave Imaging Systems With Very Sparse Array, Xiahan Yang
Doctoral Dissertations
"This dissertation investigates image reconstruction algorithms for near-field, two dimensional (2D) synthetic aperture radar (SAR) using compressed sensing (CS) based methods. In conventional SAR imaging systems, acquiring higher-quality images requires longer measuring time and/or more elements in an antenna array. Millimeter wave imaging systems using evenly-spaced antenna arrays also have spatial resolution constraints due to the large size of the antennas. This dissertation applies the CS principle to a bistatic antenna array that consists of separate transmitter and receiver subarrays very sparsely and non-uniformly distributed on a 2D plane. One pair of transmitter and receiver elements is turned on at …