Video understanding using multimodal deep learning

Video understanding using multimodal deep learning

<p>Our experience of the world is multimodal, however deep learning networks have been traditionally designed for and trained on unimodal inputs such as images, audio segments or text. In this thesis we develop strategies to exploit multimodal information (in the form of vision, text, speech a...

Disgrifiad llawn

Manylion Llyfryddiaeth
Prif Awdur:	Nagrani, A
Awduron Eraill:	Zisserman, A
Fformat:	Traethawd Ymchwil
Iaith:	English
Cyhoeddwyd:	2020
Pynciau:	Computer Vision Machine Learning

Eitemau Tebyg

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Classification of protected grassland habitats using deep learning architectures on Sentinel-2 satellite imagery data
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Computer vision and machine learning with RGB-D sensors /
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Multimodal Deep Learning Integration of Image, Weather, and Phenotypic Data Under Temporal Effects for Early Prediction of Maize Yield
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Weakly-supervised learning for video understanding
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