JOURNAL ARTICLE

Adaptive Relaxation Labeling

H. M. KalayehD. A. Landgrebe

Year: 1984 Journal:   IEEE Transactions on Pattern Analysis and Machine Intelligence Vol: PAMI-6 (3)Pages: 369-372   Publisher: IEEE Computer Society

Abstract

Current implementation of probabilistic relaxation labeling (PRL) is based on stationary compatibility coefficients (SCC's). Such labeling frequently diverges from an achieved minimum labeling error. In this correspondence it is shown that by having nonstationary compatibility coefficients (NSCC's) the PRL stabilizes about the minimum error which is obtained during the early iterations. Also, a noniterative labeling algorithm which uses NSCC and has a performance similar to that of the modified PRL is suggested.

Keywords:
Compatibility (geochemistry) Probabilistic logic Computer science Algorithm Artificial intelligence Pattern recognition (psychology) Mathematics Materials science

Metrics

14
Cited By
4.08
FWCI (Field Weighted Citation Impact)
11
Refs
0.93
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Digital Filter Design and Implementation
Physical Sciences →  Computer Science →  Signal Processing

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