Fast translation invariant classification of HRR range profiles in a zero phase representation

2003 ◽  
Vol 150 (6) ◽  
pp. 411 ◽  
Author(s):  
J. Portegies Zwart ◽  
R. van der Heiden ◽  
S. Gelsema ◽  
F. Groen
Keyword(s):  
Translation Invariant ◽  
Phase Representation ◽  
Zero Phase

scholarly journals Stamps Detection and Classification Using Simple Features Ensemble

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Paweł Forczmański ◽  
Andrzej Markiewicz
Keyword(s):  
Color Space ◽  
Shape Descriptors ◽  
Translation Invariant ◽  
Space Transformation ◽  
Rubber Stamp ◽  
Color Space Transformation ◽  
Extraction Stage ◽  
Simple Features ◽  
Scanned Documents

The paper addresses a problem of detection and classification of rubber stamp instances in scanned documents. A variety of methods from the field of image processing, pattern recognition, and some heuristic are utilized. Presented method works on typical stamps of different colors and shapes. For color images, color space transformation is applied in order to find potential color stamps. Monochrome stamps are detected through shape specific algorithms. Following feature extraction stage, identified candidates are subjected to classification task using a set of shape descriptors. Selected elementary properties form an ensemble of features which is rotation, scale, and translation invariant; hence this approach is document size and orientation independent. We perform two-tier classification in order to discriminate between stamps and no-stamps and then classify stamps in terms of their shape. The experiments carried out on a considerable set of real documents gathered from the Internet showed high potential of the proposed method.

A Scale and Translation Invariant Approach for Early Classification of Spatio-Temporal Patterns Using Spiking Neural Networks

2015 ◽  
Vol 43 (2) ◽  
pp. 327-343 ◽  
Author(s):  
Banafsheh Rekabdar ◽  
Monica Nicolescu ◽  
Mircea Nicolescu ◽  
Mohammad Taghi Saffar ◽  
Richard Kelley
Keyword(s):  
Neural Networks ◽  
Temporal Patterns ◽  
Spiking Neural Networks ◽  
Translation Invariant ◽  
Early Classification ◽  
Spatio Temporal ◽  
Invariant Approach

scholarly journals The classification of symmetry protected topological phases of one-dimensional fermion systems

2021 ◽  
Vol 9 ◽  
Author(s):  
Chris Bourne ◽  
Yoshiko Ogata
Keyword(s):  
Site Symmetry ◽  
Matrix Product ◽  
Translation Invariant ◽  
Fermion Systems ◽  
A Finite Group ◽  
Reduced Density ◽  
Symmetry Protected ◽  
Wall Group ◽  
Uniformly Bounded

Abstract We introduce an index for symmetry-protected topological (SPT) phases of infinite fermionic chains with an on-site symmetry given by a finite group G. This index takes values in $\mathbb {Z}_2 \times H^1(G,\mathbb {Z}_2) \times H^2(G, U(1)_{\mathfrak {p}})$ with a generalised Wall group law under stacking. We show that this index is an invariant of the classification of SPT phases. When the ground state is translation invariant and has reduced density matrices with uniformly bounded rank on finite intervals, we derive a fermionic matrix product representative of this state with on-site symmetry.

Translation-invariant classification of non-stationary signals

2006 ◽  
Vol 69 (7-9) ◽  
pp. 743-753 ◽  
Author(s):  
Vincent Guigue ◽  
Alain Rakotomamonjy ◽  
Stéphane Canu
Keyword(s):  
Translation Invariant ◽  
Stationary Signals
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