Visualization of Learning Processes for Back Propagation Neural Network Clustering
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 2
Abstract
Method for visualization of learning processes for back propagation neural network is proposed. The proposed method allows monitor spatial correlations among the nodes as an image and also check a convergence status. The proposed method is attempted to monitor the correlation and check the status for spatially correlated satellite imagery data of AVHRR derived sea surface temperature data. It is found that the proposed method is useful to check the convergence status and also effective to monitor the spatial correlations among the nodes in hidden layer.
Authors and Affiliations
Kohei Arai
Optical Recognition of Isolated Machine Printed Sindhi Characters using Fourier Descriptors
The scale invariance characteristics play an essential role in pattern recognition applications, for example in computer vision, OCR (Optical Character Recognition), electronic publication, etc. In this paper, the shape...
A Survey of Malware Detection Techniques based on Machine Learning
Diverse malware programs are set up daily focusing on attacking computer systems without the knowledge of their users. While some authors of these programs intend to steal secret information, others try quietly to prove...
Experimental Evaluation of the Virtual Environment Efficiency for Distributed Software Development
At every software design stage nowadays, there is an acute need to solve the problem of effective choice of libraries, development technologies, data exchange formats, virtual environment systems, characteristics of virt...
A BAYESIAN FRAMEWORK FOR GLAUCOMA PROGRESSION DETECTION USING HEIDELBERG RETINA TOMOGRAPH IMAGES
Glaucoma, the second leading cause of blindness in the United States, is an ocular disease characterized by structural changes of the optic nerve head (ONH) and changes in visual function. Therefore, early detection is o...
A New Approach for Leukemia Identification based on Cepstral Analysis and Wavelet Transform
This paper implements a new leukemia identification method which depends on Mel frequency cepstral coefficient (MFCC) feature extraction and wavelet transform. Leukemia identification is a measurement of blood cell featu...