Vol 8, No 1 (2013)
Pattern Recognition Theory
On the Analogy of Classifier Ensembles With Primary Classifiers: Statistical Performance and Optimality 98-122
Ioannis Dimou, Michalis Zervakis
The question of how we can exploit the ability to combine different learning entities is fundamental to the core of automated pattern analysis and dictates contemporary research efforts in the field of decision fusion.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.497
Applications
A System for Handwritten Script Identification From Indian Document 1-12
Obaidullah Md Sk, Supratik Kundu Das, Kaushik Roy
In a country like India a number of scripts (a total of 13) are used to write different official languages (a total of 23). For development of Optical Character Recognizer (OCR) for a particular language, the script by which the document is written is to be identified first.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.485
Kernel Non-Negative Matrix Factorization for Seismic Signature Separation 13-25
Asif Mehmood, Thyagaraju Damarla
A supervised learning algorithm for the separation of seismic sources in a single channel is presented. The proposed algorithm employs non-negative matrix factorization (NMF) technique in the feature space, called Kernel NMF (KNMF).
JPRR Vol 8, No 1 (2013); doi:10.13176/11.463
Stereo Disparity and Optical Flow Fusion by Geometric Relationship and an Efficient Recursive Algorithm 26-38
Sang Hyun Han, Sheng Yan, Hong Jeong
We suggest a relationship, called stereo-motion equation, between stereo disparity and optical flow, and a recursive filter, as an efficient algorithm to estimate the two quantities.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.210
Capped K-NN Editing in Definition Lacking Environments 39-58
Andrew Stranieri, Andrew Yatsko, Isaac Golden, Musa Mammadov, Adil Bagirov
While any input may be contributing, imprecise specification of class of data subdivided into classes identifies as rather common a source of noise.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.465
CUES: A New Hierarchical Approach for Document Clustering 66-84
Tanmay Basu, C.A. Murthy
Objective of the document clustering techniques is to assemble similar documents and segregate dissimilar documents. Unlike document classification, no labeled documents are provided in document clustering.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.459
An Image Visual Quality Assessment Method Based on SIFT Features 85-97
Guangyi Chen, Stephane Coulombe
There are a number of distortions in image acquisition, processing, compression, storage, transmission, and reproduction. Existing image metrics provide a good judgement on these image distortions.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.511
Dismount Detection Using Kernel Sparse Representation 123-131
Asif Mehmood, Jeffrey Clark, Wesam Sakla
This paper describes a new application of kernel sparse detection technique for hyperspectral imagery (HSI) in conjunction with a sequential forward feature selection (SFFS) scheme that reduces the dimensionality to a tractable volume.
JPRR Vol 8, No 1 (2013); doi:10.13176/11.528
Short Letters
Some Features of the Users' Activities in the Mobile Telephone Network 59-65
Thomas Couronné, Valery Kirzner, Katerina Korenblat, Zeev Volkovich
JPRR Vol 8, No 1 (2013); doi:10.13176/11.517