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http://20.198.91.3:8080/jspui/handle/123456789/8926Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Bhattacharjee, Debotosh | - |
| dc.contributor.author | Kumari, Ekata | - |
| dc.date.accessioned | 2025-10-13T10:34:35Z | - |
| dc.date.available | 2025-10-13T10:34:35Z | - |
| dc.date.issued | 2022 | - |
| dc.date.submitted | 2022 | - |
| dc.identifier.other | DC3558 | - |
| dc.identifier.uri | http://20.198.91.3:8080/jspui/handle/123456789/8926 | - |
| dc.description.abstract | This engineering thesis includes the approaches to implementing the Quantum Neural Networks to classify the Brain tumor on the MRI Brain Tumor dataset and the classification of digits from the MNIST database. The different architectures of Quantum Neural Network are trained on this dataset and compared in terms of prediction performance. | en_US |
| dc.format.extent | 78p. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Jadavpur University, Kolkata, West Bengal | en_US |
| dc.subject | Neural Network | en_US |
| dc.subject | MNIST | en_US |
| dc.title | Brain tumor detection using quantum neural network | en_US |
| dc.type | Text | en_US |
| dc.department | Jadavpur University, Dept. of Computer Science and Engineering | en_US |
| Appears in Collections: | Dissertations | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| M.Tech (Dept.of Computer Science and Engineering) Ekata Kumari.pdf | 12.83 MB | Adobe PDF | View/Open |
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