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14 articles for “self-organizing maps”
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Gait Based Person Identification Using Kohonen Self-Organizing Mapping Technique
Abstract: Though gait recognition system has some special security features, it has some limitations like viewing angle variation, slow or fast walk and carrying a bag etc. This paper has an advantage of removing these limitations by using gait energy image with Kohonen self-organizing mapping technique. This model proposes the method that is developed by Partial least square (PLS) used for features selection and singular value decomposition (SVD) used for dimensionality …
Published in Current Trends in Information Technology · Vol. 5, Issue 2, 2015 · pp. 1–6 Read article
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Face Recognition using Genetic Algorithm with Self-Organizing Mapping based Dimensionality Reduction Technique
Abstract: The contribution of this work is to develop a face recognition technique where Genetic Algorithm has been used. Here facial features are extracted using Active Appearance Model (AAM) and Kohonen Self-Organizing Mapping (SOM) technique has applied to reduce the dimension of the extracted features. Efficient image pre-processing techniques are used to prepare the face for the proposed system. Finally, Genetic Algorithm has been used to classify the facial features. In …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 2, Issue 1, 2015 · pp. 22–26 Read article
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Texture Segmentation Using Multichannel Filtering And Kohonen’s Self Organizing Map
Abstract: The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this paper, we implement two stage of feature extraction technique using multichannel filter and Self Organizing Map (SOM). Firstly, we go through channel filters, also known as 2-D Gabor functions. The …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 3, Issue 3, 2012 · pp. 17–30 Read article
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Feature Fusion Based Iris and Retina Recognition System Using Kohonon Self-Organizing Mapping Neural Network Algorithm
Abstract: This paper proposes a model of biometric security with feature fusion based iris and retina recognition system. Though, a lot of research works have done for iris recognition system and it is not new for the fusion of multimodal iris recognition in the area of biometric security and authentication system. But, it is a relatively new idea of mixing iris and retina features for human authentication. Here, the features of …
Published in Trends in Electrical Engineering · Vol. 5, Issue 2, 2015 · pp. 22–26 Read article
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Customer Segmentation for Enhancing Customer Centric Business
Abstract: Customer segmentation is grouping customers based on similarities so companies can approach each group for marketing effectively and appropriately. Customer segmentation is important for enhancing customer centric business for gaining retention among customers by campaigning them using better marketing strategies, causing more institutional benefit. This paper segments customers by analyzing their characteristics based on both demographic and behavioral attributes using K-Means clustering algorithm and Self-Organizing Maps (SOM). K-Means is a …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 1, 2021 · pp. 17–31 Read article
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Performance Comparison between Back-Propagation Learning and Kohonen Self-Organizing Neural Networks Algorithm in Terms of Pattern Recognition
Abstract: Pattern recognition using back-propagation learning and Kohonen self-organizing neural network algorithms has been developed and measured various performance based on different criteria and environment of the pattern. These pattern recognition systems have taken the object image as input. In image pre-processing stage, scaling and clipping process has been applied from the background image to avoid unnecessary portion of the object image. Feature extraction has been performed after applying filtering and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 1–8 Read article
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Combining the Classification of Sentiments from Opinions
Abstract: Our day-to-day life has been influenced by varied perceptions of people. Their ideas and opinions have affected our own opinions. People give their own views on the particular product or services according to their usage application. Updating of data is necessary with every passing day which results into difficulty of examining and understanding these large amounts of data. So, it becomes difficult to examine all the varied opinions and come …
Published in Journal of Advanced Database Management & Systems · Vol. 3, Issue 1, 2016 · pp. 26–29 Read article
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A Review on MR Brain Image Segmentation Based on Different Techniques
Abstract: In past few years, the growth in Magnetic Resonance Imaging (MRI) provided a new way to detect and diagnose the brain related problems such as Alzheimer, schizophrenia and brain tumor. Many supervised and unsupervised techniques are available for image segmentation. In medical field supervised and unsupervised segmentation both are available but unsupervised is in more demand then supervised because it requires external assistance. Whereas unsupervised segmentation reflects better results. In …
Published in Journal of Operating Systems Development & Trends · Vol. 2, Issue 2, 2015 · pp. 9–14 Read article
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Comparing Algorithm Performance in Machine Learning for Landslide Susceptibility Studies: An Overview
Abstract: Machine learning algorithms have gained popularity over the past years, and with this comes the rise in their efficiencies; this study demonstrated that machine learning algorithms could successfully be used to identify landslide susceptibility areas. Machine learning algorithms like decision trees, support vector machines, K-Means, Hierarchical Clustering, Self-Organizing Maps (SOMs), artificial neural networks, and Bayesian networks have been used in recent studies. This study thus reviews several studies and results …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 71–89 Read article
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Finding Color Blindness Using Ishihara Algorithm
Abstract: This paper is aimed to develop a back propagation artificial neural network (ANN) model that could distinguish crop plants from weeds. Although only the color indices associated with image pixels were used as inputs, it was assumed that the ANN model could develop the ability to use other information, such as shapes, implicit in these data. The 756x504 pixel images were taken in the field and were then cropped to …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 2, Issue 1, 2015 · pp. 1–14 Read article
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Pharmacophore Mapping of Dengue Virus Inhibitors of Natural Origin Using Phase and Self Organizing Neural Networks
Abstract: Dengue virus (DENV) infection is an important arthropod-born viral infection infecting about 2.5 billion people worldwide. To date there are no effective vaccine or antiviral treatment for dengue. Dengue patients are usually supportively treated until they recover without any specific treatment measures. Plants and plant’s derived compounds remain an important source for the discovery and the development of new antiviral drugs because of their expected low side effects and their …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 1, Issue 2, 2014 · pp. 1–18 Read article
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Automated Thyroid Nodule Detection in Ultrasound Image using Optimal Neural Network Classifier
Abstract: Malignant thyroid nodule detection is an important issue in thyroid ultrasonography image processing. Literature reports many algorithms in this domain. This research aims to design optimal decision support system (DSS) for ultrasound thyroid nodule image characterization into benign and malignant classes. Thyroid nodule region is segmented to extract texture features from thyroid nodule ultrasound images acquired from 38 patients using gray level co-occurrence matrix (GLCM) and statistical properties. These features …
Published in Journal of Advancements in Robotics · Vol. 2, Issue 2, 2015 · pp. 15–25 Read article
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Identifying Trends in Landuse/Landcover Changes in Hisar Tehsil: A LCM Based Approach
Abstract: Land is a source of all basic human needs, (e.g., agriculture, forest, water supply etc.) which is being continuously depleted by various agents. Urban growth and urbanization are considered as one of the major factors responsible for change in landcover dynamics and depletion of land resources. As compared with other landcover classes such as agricultural land, urban land has smaller area coverage but its impact to the surrounding environment is …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 1, 2017 · pp. 1–8 Read article
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Assistive Technology Advancements: Revolutionising Support for Individuals with Specific Learning Disabilities
Abstract: Assistive Technology (AT) has become an offer to revolutionise the provision of people with specific Learning Disabilities (SLD), making the learning process more inclusive and equal. In this paper, the current developments in AT will be discussed that cater to fundamental learning issues in reading, writing and mathematics. Text-to-speech and speech-to-text innovations, mind-mapping tools, and others are important innovations that improve reading comprehension and written expression, as well as strength …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article