learning vector quantization networks
Classification of meningiomas using discriminant wavelet packets and learning vector quantization
... In this paper, we have presented a novel texture based algorithm for detection and classification of meningioma images. The algorithm was based on selecting the most discriminant wavelet packet subbands and using certain ...
6
Image Contrast Enhancement using Learning Vector Quantization
... competitive learning neural networks such as the Self-Organizing Map algorithm that is a similar algorithm for unsupervised learning with the addition of connections between the ...list. ...
7
Fuzzy Modeling using Vector Quantization based on Input and Output Learning Data
... [4] S. M. Zhoua and J. Q. Ganb, Low-level interpretability and high- level interpretability: a unified view of data-driven interpretable fuzzy system modeling, Fuzzy Sets and Systems 159, pp.3091-3131, 2008. [5] K. ...
6
Fast Learning Algorithm for Fuzzy Inference Systems using Vector Quantization
... that learning method C using VQ and SDM is effective in accuracy and the number of rules to other ...a learning method of RBF networks using VQ and GIM is much fast compared to other learning ...
6
CLASSIFICATION OF DISEASED PLANT LEAVES USING NEURAL NETWORK ALGORITHMS
... (FFNN), Learning Vector Quantization (LVQ) and Radial Basis Function Networks (RBF) by processing the set of shape and texture features from the affected leaf ...machine learning based ...
7
Introduction to vector quantization and its applications for numerics*
... Neural Networks, Data Mining and, more recently, Machine Learning, as a an unsupervised clustering procedure producing prototypes and Voronoi cells (classifiers) to perform automatic classification (see ...
51
Brain MRI Classification Using PNN and Segmentation Using K Means Clustering
... Support Vector Machine (SVM), Accuracy of only 65% was ...on learning vector quantization (LVQ) with image and data analysis and manipulation techniques is proposed to carry out an automated ...
8
Survey on Effective Kidney Stone Disease Diagnosis Using ANN
... neural networks on the basis of its accuracy, time taken to build model, and training data set ...used Learning vector quantization (LVQ), two layers feed forward perceptron trained with back ...
8
Vector Quantization of True-Color Images
... the sum the of Mathematically, dimensions the product code product: m c = A C {all vectors = j=1 For with if example, rate R/k k-dimensional The product the design is a code x2'-, scalar[r] ...
119
A Review: Methods for Sensor Identification using Neural Network
... In this paper total number of sensor divided into four classes, train the neural network using learning vector Quantization, this algorithm is faster than other Algorithm. Classification of sensor ...
5
Speaker Identification by using Vector Quantization
... Dr. H. B. Kekre has received B.E. (Hons.) in Telecomm. Engg. from Jabalpur University in 1958, M.Tech (Industrial Electronics) from IIT Bombay in 1960, M.S.Engg. (Electrical Engg.) from University of Ottawa in 1965 and ...
7
ANN in Medical Field Survey Paper
... Neural Networks (ANNs) model for the selection of risk factors and the prediction of chronic diseases by taking a case study of ...neural networks provides us an effective method in the selection of risk ...
7
Image Compression Using Different Vector Quantization Algorithms and Its Comparison
... Here image compression has been appilied on six diverse 256 grey level bitmap medicinal images with 512*512 pixels. Reconstructed image quality can be assessed objectively and subjectively. In this paper, objective ...
30
A survey on neural network models for data analysis
... number of learning techniques, especially back- propagation. Here the output values are compared with the correct answer to compute the value of some predefined error-function. The error is then fed back through ...
5
Learning Vector Quantization (LVQ) Neural Network Approach for Multilingual Speech Recognition
... machine learning, speech and pattern recognition feature extraction plays a key ...the Learning Vector Quantization (LVQ) neural network for further ...
7
Multiple-Description Multistage Vector Quantization
... (MD) quantization [1, 2] has received considerable attention in recent research due to its poten- tial applications in lossy communication systems such as packet ...a vector of parameters representing a ...
7
Local Identification of Overcomplete Dictionaries
... singular vector rather than signed mean of the associated training signals, requiring K SVDs as opposed to K ...dictionary learning when the goal is compression, it brings with it some complications when ...
32
Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances
... Gauthier, F., Hétu, B., & Allard, M. (2015). Forecasting method of ice blocks fall using logistic model and melting degree–days calculation: a case study in northern Gaspésie, Québec, Canada. Natural Hazards, 79(2), ...
27
Vector Quantization of Microarray Gene Expression Data
... In the third experiment, all duplicate genes were merged together in the dataset after filling the null values with zeroes, however, this time the data was not log transformed. The LVQ1 algorithm continued dominating all ...
5
Deep Machine Learning In Neural Networks
... of accuracy. [35] In deep learning technique the compression and efficiency acts as two hands. They have used Alex net framework, in this framework consider 91% of the computation and accounts for 4% only. In ...
8