Transfer Learning by Optical Flow
| dc.contributor.advisor | Pirsiavash, Hamed | |
| dc.contributor.author | Esmaeilkhanian, Maryam | |
| dc.contributor.department | Computer Science and Electrical Engineering | |
| dc.contributor.program | Computer Science | |
| dc.date.accessioned | 2021-01-29T18:13:46Z | |
| dc.date.available | 2021-01-29T18:13:46Z | |
| dc.date.issued | 2019-01-01 | |
| dc.description.abstract | One of the biggest challenges in deep learning field of research is the need for having a large amount of annotated data. Self-supervised learning is one of the methods to tackle this issue. In this method, a new task is designed to learn features without having annotated data available. These learned features can be transferred to a new task by fine-tuning the pre-trained model. This process of transferring the learned features on one task trained on unannotated data to a new task is called transfer learning. The objective of this study is to learn low level features through novel self-supervised task, with the hypotheses being that the learned features from self-supervised task would improve object classification in the supervised learning. In addition, there is a significant reduction in the complexity of the overall model when primarily representation is learned in a deep network and the resulting knowledge is transferred to the second task. Compared to some of the existing self-supervised methods, transfer learning method described in this study is shown to have achieved superior results in terms of accuracy on object classification on PASCAL VOC 2007 dataset. | |
| dc.format | application:pdf | |
| dc.genre | theses | |
| dc.identifier | doi:10.13016/m2s0v9-iui8 | |
| dc.identifier.other | 12083 | |
| dc.identifier.uri | http://hdl.handle.net/11603/20901 | |
| dc.language | en | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Theses and Dissertations Collection | |
| dc.relation.ispartof | UMBC Graduate School Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.source | Original File Name: Esmaeilkhanian_umbc_0434M_12083.pdf | |
| dc.title | Transfer Learning by Optical Flow | |
| dc.type | Text | |
| dcterms.accessRights | Distribution Rights granted to UMBC by the author. | |
| dcterms.accessRights | Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission. | |
| dcterms.accessRights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. |