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SPIESR
2001
174views Database» more  SPIESR 2001»
13 years 11 months ago
Mapping low-level image features to semantic concepts
Humans tend to use high-level semantic concepts when querying and browsing multimedia databases; there is thus, a need for systems that extract these concepts and make available a...
Daniela Stan, Ishwar K. Sethi
ICPR
2000
IEEE
14 years 11 months ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
CVPR
2010
IEEE
14 years 2 months ago
Local Features Are Not Lonely - Laplacian Sparse Coding for Image Classification
Sparse coding which encodes the original signal in a sparse signal space, has shown its state-of-the-art performance in the visual codebook generation and feature quantization pro...
Shenghua Gao, Wai-Hung Tsang, Liang-Tien Chia, Pei...
JMM2
2006
145views more  JMM2 2006»
13 years 10 months ago
Improved Active Shape Model for Facial Feature Extraction in Color Images
In this paper we present an improved Active Shape Model (ASM) for facial features extraction. The original ASM developed by Cootes et al. [1] suffers from factors such as, poor mod...
Mohammad H. Mahoor, Mohamed Abdel-Mottaleb, A-Nass...
ICIP
2001
IEEE
14 years 11 months ago
Image data mining from financial documents based on wavelet features
In this paper, we present a framework for clustering and classifying cheque images according to their payee-line content. The features used in the clustering and classificationpro...
Ossama El Badawy, Mahmoud R. El-Sakka, Khaled Hass...