Amanote Research
Register
Sign In
Statistical Dependence of Pixel Intensities for Pattern Recognition
doi 10.1109/icit.2013.6505840
Full Text
Open PDF
Abstract
Available in
full text
Date
February 1, 2013
Authors
Ievgen Smielik
Klaus-Dieter Kuhnert
Publisher
IEEE
Related search
Bootstrap Techniques for Statistical Pattern Recognition.
Markov Logic: A Unifying Language for Structural and Statistical Pattern Recognition
Lecture Notes in Computer Science
Computer Science
Theoretical Computer Science
Comparison of Statistical Pattern-Recognition Algorithms for Hybrid Processing II Eigenvector-Based Algorithm
Journal of the Optical Society of America A: Optics and Image Science, and Vision
Pattern Recognition
Optics
Molecular Physics,
Computer Vision
Optical
Atomic
Magnetic Materials
Medicine
Electronic
A Hybrid Classification Model for Digital Pathology Using Structural and Statistical Pattern Recognition
IEEE Transactions on Medical Imaging
Electronic Engineering
Ultrasound Technology
Radiological
Computer Science Applications
Electrical
Software
Bus Real-Time Arrival Prediction Using Statistical Pattern Recognition Technique
(Statistical) Dependence
Classification of Eeg Signals for Detection of Epileptic Seizures Based on Wavelets and Statistical Pattern Recognition
Biomedical Engineering - Applications, Basis and Communications
Bioengineering
Biomedical Engineering
Biophysics
Target Differentiation With Simple Infrared Sensors Using Statistical Pattern Recognition Techniques
Pattern Recognition
Signal Processing
Computer Vision
Pattern Recognition
Artificial Intelligence
Software
A Statistical Analysis for Pattern Recognition of Small Cloud Particles Sampled With a PMS-2DC Probe
Annales Geophysicae
Planetary Sciences
Geology
Space
Atmospheric Science
Planetary Science
Astrophysics
Earth
Astronomy