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» Learning the Relative Importance of Features in Image Data
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BMCBI
2008
134views more  BMCBI 2008»
15 years 3 months ago
Identification of transcription factor contexts in literature using machine learning approaches
Background: Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While man...
Hui Yang, Goran Nenadic, John A. Keane
AIME
2009
Springer
15 years 4 months ago
Learning Approach to Analyze Tumour Heterogeneity in DCE-MRI Data During Anti-cancer Treatment
Abstract. The paper proposes a learning approach to support medical researchers in the context of in-vivo cancer imaging, and specifically in the analysis of Dynamic Contrast-Enhan...
Alessandro Daducci, Umberto Castellani, Marco Cris...
ICCV
2011
IEEE
14 years 3 months ago
Manhattan Scene Understanding Using Monocular, Stereo, and 3D Features
This paper addresses scene understanding in the context of a moving camera, integrating semantic reasoning ideas from monocular vision with 3D information available through struct...
Alex Flint, David Murray, Ian Reid
138
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CVPR
2006
IEEE
16 years 5 months ago
An Integrated Segmentation and Classification Approach Applied to Multiple Sclerosis Analysis
We present a novel multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility in detect...
Ayelet Akselrod-Ballin, Meirav Galun, Ronen Basri,...
ICMCS
2006
IEEE
145views Multimedia» more  ICMCS 2006»
15 years 9 months ago
A New Study on Distance Metrics as Similarity Measurement
Distance metric is widely used in similarity estimation. In this paper we find that the most popular Euclidean and Manhattan distance may not be suitable for all data distribution...
Jie Yu, Jaume Amores, Nicu Sebe, Qi Tian