dc.contributor.author |
Kola, Bala Murali Krishna |
|
dc.date.accessioned |
2022-03-22T09:29:17Z |
|
dc.date.available |
2022-03-22T09:29:17Z |
|
dc.date.issued |
2021-07 |
|
dc.identifier.citation |
33p. |
en_US |
dc.identifier.uri |
http://hdl.handle.net/10263/7288 |
|
dc.description |
Dissertation under the supervision of Prof. Bhabatosh Chanda |
en_US |
dc.description.abstract |
Advances in Deep Learning helped in developing exiting applications in the past
few years like Style Transfer, Image Generation. It has helped us achieving super
human performance and state-of-the-art results in various tasks like Object Recognition/
Classi cation. It has established itself as a go-to technique for solving variety
of tasks like Machine Translation in Natural Language Processing to Image Classi -
cation, Image Captioning in Computer Vision etc. Future Frame prediction is one of
the problems in Computer Vision that received a lot of interest in the recent past for
its use in Autonomous Driving, Weather Forecasting, Tra c Estimation etc. Next
Frame Prediction is the focus of this thesis. This work will explain the fundamentals
of future frame prediction and it will give an overview of existing approaches and
present an approach to solve the problem. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Indian Statistical Institute, Kolkata |
en_US |
dc.relation.ispartofseries |
Dissertation;CS-1929 |
|
dc.subject |
Video prediction |
en_US |
dc.subject |
Future frame prediction |
en_US |
dc.subject |
Convolutional LSTMs |
en_US |
dc.subject |
Long Short Term Memory networks |
en_US |
dc.subject |
Recurrent Neural Networks |
en_US |
dc.title |
Video Frame Prediction using Deep Learning |
en_US |
dc.type |
Other |
en_US |