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Fast 3D-HEVC intra-prediction for depth map based on a self-organizing map and efficient features
The ISO/IEC MPEG and ITU-T Video Coding Experts Group formed the Joint Collaborative Team on 3D Video Coding to develop the new 3D video coding...
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A highly scalable Self-organizing Map accelerator on FPGA and its performance evaluation
Self-organizing Map (SOM) is one of the artificial neural networks and well applied to datamining or feature visualization of high-dimensional...
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Breast cancer diagnosis using Stochastic Self-Organizing Map and Enlarge C4.5
Timely and accurate Breast Cancer (BC) prediction allows healthcare providers and doctors to take suitable decisions to treat the patients. Thus,...
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Predicting UPDRS in Parkinson’s disease using ensembles of self-organizing map and neuro-fuzzy
Parkinson's Disease (PD) is a complex, degenerative disease that affects nerve cells that are responsible for body movement. Artificial Intelligence...
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Annotate and retrieve in vivo images using hybrid self-organizing map
Multimodal retrieval has gained much attention lately due to its effectiveness over uni-modal retrieval. For instance, visual features often...
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A Self-Organizing Map Clustering Approach to Support Territorial Zoning
This work aims to evaluate three strategies for analyzing clusters of ordinal categorical data (thematic maps) to support the territorial zoning of...
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Prototype generation method using a growing self-organizing map applied to the banking sector
In fields like security risk analysis, Fast Moving Consumer Goods, Internet of Things, or the banking sector, it is necessary to deal with large...
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Integrating self-organizing feature map with graph convolutional network for enhanced superpixel segmentation and feature extraction in non-Euclidean data structure
Deep learning has been widely used on Euclidean data type, and the deep learning architecture has made a breakthrough by the development of...
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Self-Organizing Multi-User UAV Swarm Simulation Platform
AbstractUnmanned aerial vehicles (UAV) swarms offer a cost-effective, time-efficient data collection and analysis solution across various...
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Self-organizing speech recognition that processes acoustic and articulatory features
In automatic speech recognition (ASR) systems, the minimization of noxious effects caused by different background noises between training and...
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Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective
The automatic analysis of histology images is an open research field where machine learning techniques and neural networks, especially deep...
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Somtimes: self organizing maps for time series clustering and its application to serious illness conversations
There is demand for scalable algorithms capable of clustering and analyzing large time series data. The Kohonen self-organizing map (SOM) is an...
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Road accident risk prediction using generalized regression neural network optimized with self-organizing map
A road accident risk map that is designed to locate high-risk areas is an efficient way to reduce road traffic injuries and fatalities. To produce an...
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Self-organizing Maps
Self-organizing maps are closely related to radial basis function networks. They can be seen as radial basis function networks without an output...
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Decentralizing Self-organizing Maps
This paper presents an algorithm for a decentralized self-organizing map. With the explosion in the availability of robotics platforms, and their...
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Self-Organizing Temporally Coded Representation Learning
The self-organizing map (SOM) is an unsupervised learning algorithm that extracts representations from an input dataset and organizes them in a...
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Decision Theoretic Rough Set-Based Neighborhood for Self-Organizing Map
A decision theoretic rough set-based neighborhood selection process is developed for self-organizing maps. While the neighborhood of the winner...
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A self-organizing incremental neural network for imbalance learning
Class imbalance learning deals with data that have very skewed class distributions, and commonly exists in real-world applications. Incremental...
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An integrated approach using growing self-organizing map-based genetic K-means clustering and tolerance rough set in occupational risk analysis
To prevent the occurrences of accidents at workplaces, accident data should be analyzed properly. However, handling such data of higher dimension is...
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Some measures to impact on the performance of Kohonen self-organizing map
In the field of unsupervised learning, Self-Organizing Map (SOM) has attracted the attention of many researchers. SOM is a popular algorithm in the...
