Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/5381
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kanika | - |
dc.contributor.author | Singla, Jimmy | - |
dc.date.accessioned | 2024-04-27T05:24:10Z | - |
dc.date.available | 2024-04-27T05:24:10Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/5381 | - |
dc.language.iso | en_US | en_US |
dc.publisher | Lovely Professional University, Phagwara | en_US |
dc.subject | Computer Science and Engineering | en_US |
dc.title | Fraud detection in online transactions using deep learning techniques | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Ph.D Thesis |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
kanika thesis report final.pdf | 2.17 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.