Masters Thesis Defense for Tasmia Reza • 06/06/18 at 10:00 AM
May 22, 2018
Dear Faculty, Graduate and Undergraduate students,
You are cordially invited to my thesis defense.
Title: Object detection using feature extraction and deep learning for advanced driver assistance systems.
When: Wednesday, June 6, 2018, at 10:00 am.
Where: Simrall Hall, Room 228 (Conference Room)
Candidate: Tasmia Reza
Degree: Masters of Science, Electrical and Computer Engineering
Committee:
Dr. John E. Ball
(Major Professor)
Dr. Derek T. Anderson
(Committee Member)
Dr. Bo Tang
(Committee Member)
Abstract:
A comparison of performance between tradition support vector machine (SVM), single kernel, multiple kernel learning (MKL) and modern deep learning (DL) classifiers are observed in this thesis. The goal is to implement different machine-learning classification system for object detec tion of three-dimensional (3D) Light Detection and Ranging (LiDAR) data. The linear SVM and non-linear single kernel and MKL requires hand crafted features for training and testing their algorithm. The DL approach learns the features itself and trains the algorithm. At the end of these studies, an assessment of all the different classification methods are shown.