Search
Now showing items 41-46 of 46
Video-based Face Recognition using Deep Learning for Single Sample Per Person (SSPP) Surveillance Applications
Face Recognition (FR) is the task of identifying a person based on images of the face of the
identity. Systems for video-based face recognition in video surveillance seek to recognize
individuals of interest in real-time ...
MODEL OPTIMIZATION AND APPLICATIONS IN DEEP LEARNING
(2023-08-14)
Machine learning refers to a machine or an algorithm that draws experience from data. A certain pattern is found to build a model, which is used to solve real problems.
Deep learning, an important branch and extension ...
Deep Generative Sculpting Models for Single Image 3D Reconstruction
(2023-12-18)
In the field of computer vision, learning representations of images is an important task. This dissertation introduces deep generative sculpting models (DGSM), deep learning models that learn 3D representations of objects ...
Probabilistic Multivariate Time Series Forecasting and Robust Uncertainty Quantification with Applications in Electricity Price Prediction
(2023-12-19)
**Please note that the full text is embargoed until 02/01/2025** Electricity price forecasting (EPF) is a crucial task for market participants seeking informed decisions in day-ahead electricity markets. The increasing ...
Constructing Large Open-Source Corpora and Leveraging Language Models for Simulink Toolchain Testing and Analysis
(2023-12-06)
In several safety-critical industries such as automotive, aerospace, healthcare, and industrial automation, MATLAB/Simulink has emerged as the de-facto standard tool for system modeling and analysis, model compilation into ...
ENHANCING THE CLASSIFICATION OF AUTISM SPECTRUM DISORDER FROM RS-FMRI FUNCTIONAL CONNECTIVITY DATA USING TEMPORAL INFORMATION
(2023-12-15)
Autism Spectrum Disorder (ASD) affects the patient’s cognitive development which leads to difficulties in social functioning, daily tasks, and independent living. This necessitates intervention at an early age to take ...