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» An Evaluation on Feature Selection for Text Clustering
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EMNLP
2009
14 years 9 months ago
Automatically Evaluating Content Selection in Summarization without Human Models
We present a fully automatic method for content selection evaluation in summarization that does not require the creation of human model summaries. Our work capitalizes on the assu...
Annie Louis, Ani Nenkova
CVPR
2004
IEEE
16 years 1 months ago
Detecting and Reading Text in Natural Scenes
This paper gives an algorithm for detecting and reading text in natural images. The algorithm is intended for use by blind and visually impaired subjects walking through city scen...
Xiangrong Chen, Alan L. Yuille
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 3 days ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
ICDAR
2009
IEEE
15 years 6 months ago
Text Detection and Localization in Complex Scene Images using Constrained AdaBoost Algorithm
We have proposed a complete system for text detection and localization in gray scale scene images. A boosting framework integrating feature and weak classifier selection based on...
Shehzad Muhammad Hanif, Lionel Prevost
ICMCS
2009
IEEE
126views Multimedia» more  ICMCS 2009»
14 years 9 months ago
Sort-Merge feature selection and fusion methods for classification of unstructured video
We explore the problem of rapid automatic semantic tagging of video frames of unstructured (unedited) videos. We apply the Sort-Merge algorithm for feature selection on a large (&...
Mitchell J. Morris, John R. Kender