Deep Active Learning Explored Across Diverse Label Spaces

Deep Active Learning Explored Across Diverse Label Spaces

abstract: Deep learning architectures have been widely explored in computer vision and have depicted commendable performance in a variety of applications. A fundamental challenge in training deep networks is the requirement of large amounts of labeled training data. While gathering large quantiti...

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Bibliographic Details
Other Authors: Ranganathan, Hiranmayi (Author)
Format: Doctoral Thesis
Language:English
Published: 2018
Subjects:
Electrical engineering
Computer science
Active Learning
Deep Learning
Multiclass
Multilabel
Multimodal
Regression
Online Access:http://hdl.handle.net/2286/R.I.49076

Internet

http://hdl.handle.net/2286/R.I.49076

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