Simulations Of Implementation Of Advanced Communication Technologies, Ivy Yousuf Moutushi

Graduate Theses, Dissertations, and Problem Reports

Wireless communication systems have seen significant advancements with the introduction of 3G, 4G, and 5G mobile standards. Since the simulation of entire systems is complex and may not allow evaluation of the impact of individual techniques, this thesis presents techniques and results for simulating the performance of advanced signaling techniques used in 3G, 4G, and 5G systems, including Code division multiple access (CDMA), Multiple Input Multiple Output (MIMO) systems, and Low-Density Parity Check (LDPC) codes. One implementation issue that is explored is the use of quantized Analog to Digital Converter (ADC) outputs and their impact on system performance.

Code division …

Object Detection And Classification In The Visible And Infrared Spectrums, Domenick D. Poster

Graduate Theses, Dissertations, and Problem Reports

The over-arching theme of this dissertation is the development of automated detection and/or classification systems for challenging infrared scenarios. The six works presented herein can be categorized into four problem scenarios. In the first scenario, long-distance detection and classification of vehicles in thermal imagery, a custom convolutional network architecture is proposed for small thermal target detection. For the second scenario, thermal face landmark detection and thermal cross-spectral face verification, a publicly-available visible and thermal face dataset is introduced, along with benchmark results for several landmark detection and face verification algorithms. Furthermore, a novel visible-to-thermal transfer learning algorithm for face landmark …

Computational Mechanisms Of Face Perception, Jinge Wang

Graduate Theses, Dissertations, and Problem Reports

The intertwined history of artificial intelligence and neuroscience has significantly impacted their development, with AI arising from and evolving alongside neuroscience. The remarkable performance of deep learning has inspired neuroscientists to investigate and utilize artificial neural networks as computational models to address biological issues. Studying the brain and its operational mechanisms can greatly enhance our understanding of neural networks, which has crucial implications for developing efficient AI algorithms. Many of the advanced perceptual and cognitive skills of biological systems are now possible to achieve through artificial intelligence systems, which is transforming our knowledge of brain function. Thus, the need for …

Enhancing Vehicular Perception: A Comprehensive Analysis Of Sensor Fusion Performance Through Weighted Averages And Fuzzy C-Means For Optimal Data Association, Zachary Brian Flanigan

Graduate Theses, Dissertations, and Problem Reports

This work explores the implementation of sensor fusion and data association for autonomous vehicle design. Advancements in Adaptive Driver Assistance System (ADAS) technology have driven the development of perception algorithms required for higher levels of autonomy in vehicles. Perception algorithms process data collected from radar, camera, and LiDAR sensors to generate a complete model of the ego vehicle’s surrounding environment. Fusion of data from these sensors is important for accurate measurement of longitudinal and lateral distances to surrounding objects. Sensor fusion associates sensor detections to each other through different data association techniques. Data association techniques can consist of independent assignment …