| Titre : | Parallel implementation of Kohonen maps for color image clustering |
| Auteurs : | Ababou Abdelkader, Auteur ; Djelloul Mokadem, Directeur de thèse |
| Type de document : | texte imprimé |
| Editeur : | 3- University Of Saïda- Dr Moulay Tahar Technology Faculty Department of Process Engineering, 2017/2018 |
| Format : | 78 p |
| Langues: | Français |
| Catégories : | |
| Mots-clés: | Self-Organizing Map ; neural networks ; Color images segmen- tation ; Parallel learning algorithms ; Data Mining ; Image clustering |
| Résumé : |
Artificial neural networks (ANN) represent a universal model, which can be
leveraged to solve a great variety of tasks. The latest research showed a significant progress of this field in the past few decades. After the paral- lel hardware became available for reasonable prices, it fueled the research of efficient optimization of ANN by leveraging parallel architectures. In this thesis , We present parallel implementation of Kohonens Self-Organizing Map (SOM) neural network for segmentation of color images.The efficiency of the implemented confirmed by the results of the performed tests |
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Parallel implementation of Kohonen maps for color image clustering Adobe Acrobat PDF |
