| dc.contributor.author | Medhi, Moushumi | |
| dc.date.accessioned | 2026-09-18T12:18:03Z | |
| dc.date.available | 2026-09-18T12:18:03Z | |
| dc.date.issued | 2026-06 | |
| dc.identifier.govdoc | NB19402 | |
| dc.identifier.uri | http://127.0.0.1/xmlui/handle/123456789/17798 | |
| dc.language.iso | en | en_US |
| dc.publisher | IIT Kharagpur | en_US |
| dc.subject | Depth Map Completion | en_US |
| dc.subject | Microsoft Kinect Sensor | en_US |
| dc.subject | Lidar Scanner | en_US |
| dc.subject | RGB-D Data | en_US |
| dc.subject | Generative Adversarial Network | en_US |
| dc.title | Harnessing Deep Learning Methods for Depth Completion in Resource-Constrained Environments | en_US |
| dc.type | Thesis | en_US |