A multi-view embedding space for modeling internet images, tags, and their semantics
This paper investigates the problem of modeling Internet images and associated text or tags
for tasks such as image-to-image search, tag-to-image search, and image-to-tag search …
for tasks such as image-to-image search, tag-to-image search, and image-to-tag search …
Personalized vocabulary for digital assistant
LH Chen, AJ Cheyer, DR Guzzoni… - US Patent 8,903,716, 2014 - Google Patents
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Service orchestration for intelligent automated assistant
AJ Cheyer, DR Guzzoni, TR Gruber… - US Patent …, 2014 - Google Patents
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Multitask spectral clustering by exploring intertask correlation
Clustering, as one of the most classical research problems in pattern recognition and data
mining, has been widely explored and applied to various applications. Due to the rapid …
mining, has been widely explored and applied to various applications. Due to the rapid …
Semantic preserving distance metric learning and applications
How do we accurately browse a large set of images or efficiently annotate the images from
an image library? Image clustering methods are invaluable tools for applications such as …
an image library? Image clustering methods are invaluable tools for applications such as …
The national cancer informatics program (NCIP) annotation and image markup (AIM) foundation model
P Mongkolwat, V Kleper, S Talbot, D Rubin - Journal of digital imaging, 2014 - Springer
Abstract Knowledge contained within in vivo imaging annotated by human experts or
computer programs is typically stored as unstructured text and separated from other …
computer programs is typically stored as unstructured text and separated from other …
Social image tagging with diverse semantics
We have witnessed the popularity of image-sharing websites for sharing personal
experiences through photos on the Web. These websites allow users describing the content …
experiences through photos on the Web. These websites allow users describing the content …
Multi-graph-view learning for graph classification
Graph classification has traditionally focused on graphs generated from a single feature
view. In many applications, it is common to have useful information from different …
view. In many applications, it is common to have useful information from different …
Multi-graph learning with positive and unlabeled bags
In this paper, we formulate a new multi-graph learning task with only positive and unlabeled
bags, where labels are only available for bags but not for individual graphs inside the bag …
bags, where labels are only available for bags but not for individual graphs inside the bag …
Content-based image ranking
Methods, systems, and apparatus, including computer program products, for ranking search
results for queries. The method includes calculating a visual similarity score for one or more …
results for queries. The method includes calculating a visual similarity score for one or more …