Vector quantization of images using modified adaptive resonance algorithm for hierarchical clustering

IEEE Transactions on Neural Networks

Volumn 12, Issue 5, 2001, Pages 1147-1162

  Vlajic, Natalija ^b   Card, Howard C ^a,c  

^a IEEE   (Canada)

^b UNIVERSITY OF OTTAWA   (Canada)

^c UNIVERSITY OF MANITOBA   (Canada)

Author keywords

Data processing; Image compression; Unsupervised neural network (NN) learning

Indexed keywords

HIERARCHICAL CLUSTERING; MODIFIED ADAPTIVE RESONANCE ALGORITHM; UNSUPERVISED NEURAL NETWORKS LEARNING;

COMPUTER SIMULATION; IMAGE CODING; IMAGE COMPRESSION; IMAGE QUALITY; JAVA PROGRAMMING LANGUAGE; LEARNING ALGORITHMS; LEARNING SYSTEMS; VECTOR QUANTIZATION;

NEURAL NETWORKS;

EID: 0035441173     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.950143     Document Type: Article

References (13)

1. ART2: Self-organization of stable category recognition codes for analog input patterns
2. Adaptive algorithms for hypertext clustering
3. Generalized clustering networks and Kohonen's self-organizing scheme
4. A growing and splitting elastic network for vector quantization
5. Application of neural 'gas' model in image compression
6. Design of vector quantization networks by MDL-based principles
7. Some competitive learning methods