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» Annotator Rationales for Visual Recognition
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IJCV
2011
264views more  IJCV 2011»
13 years 2 months ago
Cost-Sensitive Active Visual Category Learning
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
Sudheendra Vijayanarasimhan, Kristen Grauman
CHI
2007
ACM
14 years 7 months ago
Getting our head in the clouds: toward evaluation studies of tagclouds
Tagclouds are visual presentations of a set of words, typically a set of "tags" selected by some rationale, in which attributes of the text such as size, weight, or colo...
A. W. Rivadeneira, Daniel M. Gruen, Michael J. Mul...
CVPR
2010
IEEE
14 years 9 days ago
Visual Recognition using Mappings that Replicate Margins
We consider the problem of learning to map between two vector spaces given pairs of matching vectors, one from each space. This problem naturally arises in numerous vision problem...
Lior Wolf, Nathan Manor
JCDL
2006
ACM
140views Education» more  JCDL 2006»
14 years 1 months ago
Exploring erotics in Emily Dickinson's correspondence with text mining and visual interfaces
This paper describes a system to support humanities scholars in their interpretation of literary work. It presents a user interface and web architecture that integrates text minin...
Catherine Plaisant, James Rose, Bei Yu, Loretta Au...
ICCV
2011
IEEE
12 years 7 months ago
Actively Selecting Annotations Among Objects and Attributes
We present an active learning approach to choose image annotation requests among both object category labels and the objects’ attribute labels. The goal is to solicit those labe...
Adriana Kovashka, Sudheendra Vijayanarasimhan, Kri...