Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/446132
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2023-01-13T16:47:26Z | - |
dc.date.available | 2023-01-13T16:47:26Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/446132 | - |
dc.description.abstract | newline | |
dc.format.extent | xvi., 122 pages | |
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Deep Convolutional Neural Networks for Single Image Super Resolution and Compression Artifacts Reduction | |
dc.title.alternative | ||
dc.creator.researcher | Amaranageswarao., Gadipudi | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.description.note | ||
dc.contributor.guide | S., Deivalakshmi | |
dc.publisher.place | Tiruchirappalli | |
dc.publisher.university | National Institute of Technology Tiruchirappalli | |
dc.publisher.institution | Department of Electronics and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2021 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Electronics and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 89.61 kB | Adobe PDF | View/Open |
02_prelim.pdf | 163.82 kB | Adobe PDF | View/Open | |
03_content.pdf | 30.77 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 30.16 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 48.67 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 43.77 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 594.67 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 527.63 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 558.95 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 2.27 MB | Adobe PDF | View/Open | |
11_annexures.pdf | 70.51 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 116.5 kB | Adobe PDF | View/Open |
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