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Hierarchical Learning of Discriminative Features and Classifiers for Large-scale Visual Recognition
Title
Hierarchical Learning of Discriminative Features and Classifiers for Large-scale Visual Recognition
Author
Zhou, Ning
Date Created
2014
Subjects--Topical
Computer science
Description
Enabling computers to recognize objects present in images has been a long standing but tremendously challenging problem in the field of computer vision for decades. Beyond the difficulties resulting from huge appearance variations, large-scale vis...
Large-scale image collection cleansing, summarization and exploration
Title
Large-scale image collection cleansing, summarization and exploration
Author
Yang, Chunlei
Date Created
2012
Subjects--Topical
Computer science
Description
A perennially interesting topic in the research field of large scale image collection organization is how to effectively and efficiently conduct the tasks of image cleansing, summarization and exploration. The primary objective of such an image or...
A STOCHASTIC SEGMENTATION METHOD FOR INTERESTING REGION DETECTION AND IMAGE RETRIEVAL
Title
A STOCHASTIC SEGMENTATION METHOD FOR INTERESTING REGION DETECTION AND IMAGE RETRIEVAL
Author
Li, Zhong
Date Created
2009
Subjects--Topical
Computer science, Information science
Description
The explosively increasing digital photo urges for an efficient image retrieval system so that digital images can be organized, shared, and reused. Current content based image retrieval (CBIR) systems face multiple challenges in all aspects: image...
Structural Learning for Large Scale Image Classification
Title
Structural Learning for Large Scale Image Classification
Author
Shen, Yi
Date Created
2013
Subjects--Topical
Computer science
Description
To leverage large-scale collaboratively-tagged (loosely-tagged) images for training a large number of classifiers to support large-scale image classification, we need to develop new frameworks to deal with the following issues: (1) spam tags, i.e....
Representation Learning of Image Recognition: Diversity, Aspect Ratio, Invariance, and Composition
Title
Representation Learning of Image Recognition: Diversity, Aspect Ratio, Invariance, and Composition
Author
Chen, Qiuyu
Date Created
2021
Subjects--Topical
Computer science
Description
Deep neural networks (DNN) are proved to be effective and improve the performance dramatically in various kinds of computer vision tasks. The end-to-end learning manner in training DNN consistently shows the powerful modeling ability and consequen...