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» Extracting Important Sentences with Support Vector Machines
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ISBI
2011
IEEE
12 years 11 months ago
Network cycle features: Application to computer-aided Gleason grading of prostate cancer histopathological images
Features extracted from cell networks have become popular tools in histological image analysis. However, existing features do not take sufficient advantage of the cycle structure...
Parmeshwar Khurd, Leo Grady, Ali Kamen, Summer Gib...
MICCAI
2006
Springer
14 years 8 months ago
Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions
Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of contractions and to analyze the intestine motility. Feat...
Fernando Azpiroz, Fernando Vilariño, Jordi ...
MLDM
2005
Springer
14 years 1 months ago
Low-Level Cursive Word Representation Based on Geometric Decomposition
Abstract. An efficient low-level word image representation plays a crucial role in general cursive word recognition. This paper proposes a novel representation scheme, where a word...
Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen, Domi...
IJBRA
2010
133views more  IJBRA 2010»
13 years 4 months ago
Scalable biomedical Named Entity Recognition: investigation of a database-supported SVM approach
This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features and ...
Mona Soliman Habib, Jugal Kalita
BMCBI
2008
149views more  BMCBI 2008»
13 years 7 months ago
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach ...
Antti Airola, Sampo Pyysalo, Jari Björne, Tap...