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149 results for “Neural Network Classification”
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Research ArticleOpen accessEvery word in the titleNew Constructive Neural Network Architecture for Pattern ClassificationS. S. Sridhar, M. PonnavaikkoProblem statement: Constructive neural network learning algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. These algorithms initially start with small network and dynamically allow the network to grow by adding and training neurons as needed until a satisfactory solution is found. The … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,565 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleBack Propagation Neural Network Arabic Characters Classification Module Utilizing Microsoft WordA. A. HamzaProblem statement: Arabic character recognition has been one of the last major languages to receive attention. This may be attributed to the inherent complexity of both printed and handwritten Arabic characters. The objectives of this study were to: (i) summarize the main characteristics of Arabic language writing style. (ii) suggest a neural network recognition circuit. Approach: A Neural network with … …Journal of Computer Science, Vol. 4, Issue 9 · 30 Sep 2008 · 7,831 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFunctional Link Artificial Neural Network for Classification Task in Data MiningB. B. Misra, S. DehuriIn solving classification task of data mining, the traditional algorithm such as multi-layer perceptron takes longer time to optimize the weight vectors. At the same time, the complexity of the network increases as the number of layers increases. In this study, we have used Functional Link Artificial Neural Networks (FLANN) for the task of classification. In contrast to multiple layer … …Journal of Computer Science, Vol. 3, Issue 12 · 31 Dec 2007 · 60,797 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAdaptive Resonance Theory 1 (ART1) Neural Network Based Horizontal and Vertical Classification of 0-9 Digits RecognitionMbaitiga ZacharieThis study describes the Adaptive Resonance Theory 1 (ART1), an efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART neural network architecture for horizontal and vertical classification of 0-9 digits recognition. In our approach the ART1 model can self-organize in real time producing stable and clear recognition while getting input patterns beyond those originally … …Journal of Computer Science, Vol. 3, Issue 11 · 30 Nov 2007 · 7,346 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification of X-Ray Images Using Convolutional Neural Network and Automatic Hyper-Parameter Selection to Detect Tuberculosis (TB)Biswaranjan Debata, Rojalina Priyadarshini, Sudhir Kumar Mohapatra, Tarikwa Tesfa BedaneTuberculosis (TB) is a major public health issue in India, contributing significantly to the global burden of respiratory diseases. This study introduces a Convolutional Neural Network (CNN)--based model for the early and cost-effective detection of TB using chest X-ray images. The proposed model, featuring 13 layers and automated hyperparameter selection, classifies images as infected or not infected. It is evaluated … …Journal of Computer Science, Vol. 21, Issue 2 · 21 Jan 2025 · 6,983 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification of Geographical Land Structure Using Convolution Neural Network and Transfer LearningMustafa Majeed Abd Zaid, Ahmed Abed Mohammed, Putra SumariSatellite imagery has dramatically revolutionized the field of geography by giving academics, scientists, and policymakers unprecedented global access to spatial data. Manual methods typically require significant time and effort to detect the generic land structure in satellite images. This study can produce a set of applications such as urban planning and development, environmental monitoring, disaster management, etc. Therefore, the research … …Journal of Computer Science, Vol. 20, Issue 12 · 24 Oct 2024 · 5,079 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Convolutional Neural Network Approach for Skin Lesion Classification Using Imbalanced Dataset with Image AugmentationZhyar Yassin Abdalla, Nor Hazlyna Harun, Mohammed Shihab AhmedA significant threat to people's health all over the world is skin cancer. The purpose of this research is to improve the detection of skin cancer by utilizing a CNN classification model that makes use of preprocessing and augmentation techniques. The HAM10000 dataset is used, and the imbalance it contains is addressed by resizing the images to 120×120 pixels and … …Journal of Computer Science, Vol. 20, Issue 11 · 10 Sep 2024 · 5,427 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComputer Users Sitting Posture Classification Using Distinct Feature Points and Small Scale Convolutional Neural Network for Humana Computer Intelligent Interactive System During COVID-19Jheanel Estrada, Larry VeaThe sudden change in our workplace practices from face-to-face work to work from home setup due to the pandemic has brought positive and negative impacts on our overall health. In literature, the use of deep learning and specialized cameras in the estimation of the human pose is popular even if there is a need for high computational resources and complex … …Journal of Computer Science, Vol. 19, Issue 4 · 16 Mar 2023 · 6,553 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification of Transformed and Geometrically Distorted Images using Convolutional Neural NetworkSanad Aburass, Ammar Huneiti, Mohammad Belal Al-ZoubiConvolutionalNeural Network is a deep learning method that is used in many image-relatedapplications, such as image recognition and classification, it has achievedgreat performance in these fields, but it still suffers from some shortcomings.One of these shortcomings is not being able to be invariant to the input datadue to some image transformations like translation, rotation, scaling, andgeometric distortions such as skewness, … …Journal of Computer Science, Vol. 18, Issue 8 · 26 Aug 2022 · 6,138 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification Program and Story Boundaries Segmentation in TV News Broadcast Videos via Deep Convolutional Neural NetworkMounira Hmayda, Ridha Ejbali, Mourad ZaiedGiven the amount of video information on the net, the user has had difficulty finding the information in a reasonable amount of time. Thus, all video content must be segmented and annotated so that he/she can access the information directly. The goal of the proposed approach is to allow a better exploitation of video by multimedia services (TV-On- Demand, catch-up … …Journal of Computer Science, Vol. 16, Issue 5 · 14 May 2020 · 7,743 accessesView PDFCite