Date of Award
Spring 2017
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Computing Sciences - (Ph.D.)
Department
Computer Science
First Advisor
Chengjun Liu
Second Advisor
James Geller
Third Advisor
Ali Mili
Fourth Advisor
Taro Narahara
Fifth Advisor
Zhi Wei
Abstract
Visual recognition is one of the most difficult and prevailing problems in computer vision and pattern recognition due to the challenges in understanding the semantics and contents of digital images. Two major components of a visual recognition system are discriminatory feature representation and efficient and accurate pattern classification. This dissertation therefore focuses on developing new learning methods for visual recognition.
Recommended Citation
Liu, Qingfeng, "Investigation of new learning methods for visual recognition" (2017). Dissertations. 20.
https://digitalcommons.njit.edu/dissertations/20
