| Type of Material: | Thesis |
| Title: | Deep learning approaches for scenario based abnormality detection in video surveillance system |
| Researcher: | Kuppa, S. |
| Guide: | Suresha, M. |
| Department: | Department of Computer Science |
| Publisher: | Kuvempu University, Shimoga |
| Place: | Shimoga |
| Year: | 2026 |
| Language: | English |
| Subject: | Deep Learning | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Computer Science, Kuvempu University, Shimoga, Shimoga; 2026 |
| 003 | IN-AhILN | |
| 005 | 2026-09-16 11:13:51 | |
| 008 | __ | 260916t2026||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_463111 |
| 040 | __ | |aKVMP_577451|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aKuppa, S.|eResearcher |
| 110 | __ | |aDepartment of Computer Science|bKuvempu University, Shimoga|dShimoga|ein|0U-0232 |
| 245 | __ | |aDeep learning approaches for scenario based abnormality detection in video surveillance system |
| 260 | __ | |aShimoga|c2026|bKuvempu University, Shimoga |
| 502 | __ | |bPhD|cDepartment of Computer Science, Kuvempu University, Shimoga, Shimoga|d2026 |
| 518 | __ | |oDate of Notification|d2026-09-03 |
| 518 | __ | |oDate of Completion|d2026-09-03 |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aDeep Learning |
| 700 | __ | |aSuresha, M.|eGuide |
| 905 | __ | |anotification |
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