Sports Video Action Recognition
| dc.contributor.author | Datta, Santanu | |
| dc.date.accessioned | 2022-01-28T05:24:11Z | |
| dc.date.available | 2022-01-28T05:24:11Z | |
| dc.date.issued | 2019-06-30 | |
| dc.description | Dissertation under the supervision of Prof. Kumar Sankar Ray | en_US |
| dc.description.abstract | From playing games to driving cars, deep learning has achieved great success in the recent past.In this dissertation, we apply deep learning to recognize sports videos. We have implemented state of the art VGG3D model on different challenging state of the art video datasets. In this paper , we communicate our findings. | en_US |
| dc.identifier.citation | 45p. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10263/7249 | |
| dc.language.iso | en | en_US |
| dc.publisher | Indian Statistical Institute, Kolkata | en_US |
| dc.relation.ispartofseries | Dissertation;;2019:4 | |
| dc.subject | Action recognition | en_US |
| dc.subject | Deep Learning | en_US |
| dc.title | Sports Video Action Recognition | en_US |
| dc.type | Other | en_US |
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