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Histogram of Low-Level Visual Features for Salient Feature Extraction

Arabian Journal for Science and Engineering, 2022
Rubab Mehboob   +3 more
openaire   +1 more source

Quadratic-chi similarity metric learning for histogram feature

The First Asian Conference on Pattern Recognition, 2011
Histogram features, such as SIFT, HOG, LBP et al, are widely used in modern computer vision algorithms. According to [18], chi-square distance is an effective measure for comparing histogram features. In this paper, we propose a new method, named the Quadric-chi similarity metric learning (QCSML) for histogram features.
null Xinyuan Cai   +3 more
openaire   +1 more source

Fermat theorem and elliptic color histogram features

2003
Color histograms are widely used for content-based image retrieval. Their advantages are efficiency, and insensitivity to small changes in camera viewpoint. However, a histogram is a coarse characterization of an image, and so images with very different appearances can have similar histograms.
Cinque L.   +3 more
openaire   +1 more source

Histogram Features Extraction for Edge Detection Approach

2022 5th International Conference on Engineering Technology and its Applications (IICETA), 2022
Fallah H. Najjar   +5 more
openaire   +1 more source

Histogram-Based Feature Selection for Binary Classification

This paper presents a novel method for feature selection in binary classification tasks based on histogram-based scoring. By leveraging the distribution differences between feature values associated with positive and negative classes, we generate a score to determine the most informative features.
Delil, Selman   +2 more
openaire   +1 more source

Relative gradient histogram features for face recognition

Optics and Precision Engineering, 2014
杨利平 YANG Li-ping   +1 more
openaire   +1 more source

Gastroenteropancreatic Neuroendocrine Tumors

Ca-A Cancer Journal for Clinicians, 2018
Mauro Cives
exaly  

Patient adherence and persistence with oral anticancer treatment

Ca-A Cancer Journal for Clinicians, 2009
Kathryn J Ruddy, Ann H Partridge
exaly  

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