Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/468666
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | An optimized deep learning model for Brain tumor segmentation and Classification | |
dc.date.accessioned | 2023-03-14T07:11:52Z | - |
dc.date.available | 2023-03-14T07:11:52Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/468666 | - |
dc.format.extent | xv,123p. | |
dc.language | English | |
dc.relation | p.112-122 | |
dc.rights | university | |
dc.title | An optimized deep learning model for Brain tumor segmentation and Classification | |
dc.title.alternative | ||
dc.creator.researcher | Rajaragavi, R | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.subject.keyword | Brain tumor | |
dc.subject.keyword | segmentation | |
dc.subject.keyword | optimized deep | |
dc.description.note | ||
dc.contributor.guide | Palanivel rajan, S | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2022 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | 21cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 23.09 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 2.12 MB | Adobe PDF | View/Open | |
03_content.pdf | 14.67 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 6.85 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 364.53 kB | Adobe PDF | View/Open | |
06-chapter 2.pdf | 261.12 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 639.9 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 697.27 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 632 kB | Adobe PDF | View/Open | |
10_annexures.pdf | 146.99 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 100.3 kB | Adobe PDF | View/Open |
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