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Prediction of Activity Durations in Ubiquitous Sensor Data Using Bi-Directional LSTM by Amulya Rawat

By:

Rawat, Amulya

Contributor(s):

Banerjee, Dip Sankar

Material type: Text

Text

TextPublication details: IIT Jodhpur Department of Computer Science and Engineering 2021Description: vii;20pSubject(s):

DDC classification:

006.3 R257P

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Holdings
Item type	Home library	Call number	Status	Date due	Barcode	Item holds
Thesis	S. R. Ranganathan Learning Hub	006.3 R257P (Browse shelf(Opens below))	Not for loan		TM00263

Total holds: 0

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Previous	006.3 G231G Grammatical Error Correction for Indian Languages	006.3 H489S Semantic Occupancy Grid Maps for Domestic Robots	006.3 L847P Predictive Maintenance of High Value Assets using Machine Learning Techniques	006.3 R257P Prediction of Activity Durations in Ubiquitous Sensor Data Using Bi-Directional LSTM	006.3 R911A Artificial Intelligence A modern approach	006.3 S131E Explainability Inspires Learning: Making Deep Learning Models Robust Against Occlusions	006.3 S531W Windmill System Failure Prediction using Image Processing	Next

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