Elements of information theory
Elements of information theory
GTM: the generative topographic mapping
Neural Computation
Visual information retrieval
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-based query of image databases: inspirations from text retrieval
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Principles of visual information retrieval
Principles of visual information retrieval
Generative probability density model in the self-organizing map
Self-Organizing neural networks
Self-Organizing Maps
Image Databases: Search and Retrieval of Digital Imagery
Image Databases: Search and Retrieval of Digital Imagery
Implementing Relevance Feedback as Convolutions of Local Neighborhoods on Self-Organizing Maps
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Using Smoothed Data Histograms for Cluster Visualization in Self-Organizing Maps
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Integrating contextual information to enhance SOM-based text document clustering
Neural Networks - New developments in self-organizing maps
Introduction to MPEG-7: Multimedia Content Description Interface
Introduction to MPEG-7: Multimedia Content Description Interface
An efficiency comparison of two content-based image retrieval systems, GIFT and PicSOM
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
IEEE Transactions on Image Processing
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
PicSOM-self-organizing image retrieval with MPEG-7 content descriptors
IEEE Transactions on Neural Networks
A nonlinear projection method based on Kohonen's topology preserving maps
IEEE Transactions on Neural Networks
Computer Vision and Image Understanding
Rushes summarization with self-organizing maps
Proceedings of the international workshop on TRECVID video summarization
Perplexity-based evidential neural network classifier fusion using mpeg-7 low-level visual features
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Optimal Combination of SOM Search in Best-Matching Units and Map Neighborhood
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Learning a Self-organizing Map Model on a Riemannian Manifold
Proceedings of the 13th IMA International Conference on Mathematics of Surfaces XIII
Computer Vision and Image Understanding
Probabilistic PCA self-organizing maps
IEEE Transactions on Neural Networks
Multivariate Student-t self-organizing maps
Neural Networks
Media map: a multilingual document map with a design interface
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Semantic annotation of image groups with self-organizing maps
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Adaptive timeline interface to personal history data
Proceedings of the 15th ACM on International conference on multimodal interaction
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A Self-Organizing Map (SOM) is typically trained in unsupervised mode, using a large batch of training data. If the data contain semantically related object groupings or classes, subsets of vectors belonging to such user-defined classes can be mapped on the SOM by finding the best matching unit for each vector in the set. The distribution of the data vectors over the map forms a two-dimensional discrete probability density. Even from the same data, qualitatively different distributions can be obtained by using different feature extraction techniques.We used such feature distributions for comparing different classes and different feature representations of the data in the context of our content-based image retrieval system PicSOM. The information-theoretic measures of entropy and mutual information are suggested to evaluate the compactness of a distribution and the independence of two distributions. Also, the effect of low-pass filtering the SOM surfaces prior to the calculation of the entropy is studied.