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We introduce in this paper a novel approach to multi-label image classification which incorporates a new type of context — label exclusive context — with linear representation and classification. Given a set of exclusive label groups that describe the negative relationship among class labels, our method, namely LELR for Label Exclusive Linear(More)
Annotating large-scale image corpus requires huge amount of human efforts and is thus generally unaffordable, which directly motivates recent development of semi-supervised or active annotation methods. In this paper we revisit this notoriously challenging problem and develop a novel multi-label propagation scheme, whereby both the efficacy and accuracy of(More)
This paper describes our system for auto search and interactive search in the known-item search (KIS) task in TRECVID 2010. KIS task aims to find an unique video answer for each text query. The shift from traditional video search has prompted a series of challenges in processing and searching techniques that developed over the past few years. For the(More)
During chronic viral infection, virus-specific CD8(+) T cells become exhausted, exhibit poor effector function and lose memory potential. However, exhausted CD8(+) T cells can still contain viral replication in chronic infections, although the mechanism of this containment is largely unknown. Here we show that a subset of exhausted CD8(+) T cells expressing(More)
Glaucoma is a chronic and irreversible eye disease, which leads to deterioration in vision and quality of life. In this paper, we develop a deep learning (DL) architecture with convolutional neural network for automated glaucoma diagnosis. Deep learning systems, such as convolutional neural networks (CNNs), can infer a hierarchical representation of images(More)
In recent years, locality-sensitive hashing (LSH) has gained plenty of attention from both the multimedia and computer vision communities due to its empirical success and theoretic guarantee in large-scale visual indexing and retrieval. Conventional LSH algorithms are designated either for generic metrics such as Cosine similarity, &ell;<sub>2</sub>-norm(More)
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract We have successfully experimentally integrated graphene(More)
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract—Carbon-based nanomaterials such as metallic single-walled carbon(More)
In the past decade, locality-sensitive hashing (LSH) has gained a large amount of attention from both the multimedia and computer vision communities owing to its empirical success and theoretic guarantee in large-scale multimedia indexing and retrieval. Original LSH algorithms are designated for generic metrics such as Cosine similarity, $$\ell _2$$ -norm(More)