자료유형 | E-Book |
---|---|
개인저자 | Kabkab, Maya. |
단체저자명 | University of Maryland, College Park. Electrical Engineering. |
서명/저자사항 | Learning Along the Edge of Deep Neural Networks. |
발행사항 | [S.l.] : University of Maryland, College Park., 2018 |
발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
형태사항 | 157 p. |
소장본 주기 | School code: 0117. |
ISBN | 9780438144613 |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Rama Chellappa. |
요약 | While Deep Neural Networks (DNNs) have recently achieved impressive results on many classification tasks, it is still unclear why they perform so well and how to properly design them. It has been observed that while training and testing deep net |
요약 | In this dissertation, we analyze each of these individual conditions to understand their effects on the performance of deep networks. Furthermore, we devise mitigation strategies when the ideal conditions may not be met. |
요약 | We, first, investigate the relationship between the performance of a convolutional neural network (CNN), its depth, and the size of its training set. Designing a CNN is a challenging task and the most common approach to picking the right archite |
요약 | Next, we study the structure of the CNN layers, by examining the convolutional, activation, and pooling layers, and showing a parallelism between this structure and another well-studied problem: Convolutional Sparse Coding (CSC). The sparse repr |
요약 | Then, we investigate three of the ideal conditions previously mentioned: the availability of vast amounts of noiseless and balanced training data. We overcome the difficulties resulting from deviating from this ideal scenario by modifying the tr |
요약 | Finally, we consider the case where testing (and potentially training) samples are lossy, leading to the well-known compressed sensing framework. We use Generative Adversarial Networks (GANs) to impose structure in compressed sensing problems, r |
일반주제명 | Computer science. Electrical engineering. Artificial intelligence. |
언어 | 영어 |
기본자료 저록 | Dissertation Abstracts International79-12B(E). Dissertation Abstract International |
대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14997306 |
인쇄
No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
---|---|---|---|---|---|---|---|---|
1 | WE00026725 | 004 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |