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59 results for “neural network classifier”

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Research ArticleOpen accessIn the abstractAn Overview of Research Challenges for Classification of Cardiotocogram DataC. Sundar, M. Chitradevi, G. GeetharamaniCardiotocography (CTG) is a simultaneous recording of Fetal Heart Rate (FHR) and Uterine Contractions (UC). The most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. By observing the Cardiotocography trace patterns doctors can understand the state of the fetus. There are several signal processing and computer programming based techniques for interpreting a typical Cardiotocography … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,827 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Ensemble Prediction Algorithms for Detecting Faulty Modules in Object Oriented Systems Using Quality MetricsM. Punithavalli, C. NeelamegamThe high usage of software system poses high quality demand from users, which results in increased software complexity. To address these complexities, software quality engineering methods should be updated accordingly and enhance their quality assuring methods. Fault prediction, a sub-task of SQE, is designed to solve this issue and provide a strategy to identify faulty parts of a program, so … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,435 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Improved Approach for Detecting Car in Video using Neural Network ModelS. N. Sivanandam, T. Senthil KumarThe study represents a novel approach taken towards car detection, feature extraction and classification in a video. Though many methods have been proposed to deal with individual features of a vehicle, like edge, license plate, corners, no system has been implemented to combine features. Combination of four unique features, namely, color, shape, number plate and logo gives the application a … …Journal of Computer Science, Vol. 8, Issue 10 · 1 Sep 2012 · 7,151 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Adaptive Neuro-Fuzzy Inference System for Information SecuirtyAltyeb Altaher, Ammar Almomani, Sureswaran RamadassProblem statement: Computer networks are expanding at very fast rate and the number of network users is increasing day by day, for full utilization of networks it need to be secured against many threats including malware, which is harmful software with the capability to damage data and systems. Fuzzy rule based classification systems considered as an active research area in … …Journal of Computer Science, Vol. 8, Issue 6 · 23 Apr 2012 · 7,747 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hidden Genetic Layer Based Neural Network for Mobility PredictionL. Velmurugan, P. ThangarajProblem statement: With numerous wireless devices increasingly connecting to the internet, WLAN infrastructure planning becomes very important to maintain desired quality of services. For maintaining desired quality of service it is desirable to know the movement pattern of users. Mobility prediction involves finding the mobile device's next access point as it moves through the wireless network. Hidden Markov models and … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 11 Feb 2012 · 7,224 accessesView PDFCite
Research ArticleOpen accessIn the abstractStill Image Compression Using Texture and Non Texture Prediction ModelG. Mohanbaabu, P. RenugaProblem statement: Existing lossless image compression schemes attempt to do prediction in an image data using their Local Binary Pattern (LBP) and their spatial neighborhood based techniques. In the previous techniques such as Vector Quantization (VQ) and Gradient Adjusted Prediction (GAP) the texture and non-texture regions are not classified separately. Texture and Non-texture images prophecy has been a key factor … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 11 Feb 2012 · 7,303 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Reduction Algorithm for Analysis of Linear NeuronMohammad Dweib, Yousef AbuzirProblem statement: The aim of feature selection is to select a feature set that is relevant for a given application. Feature selection is complex and remains an important issue in many domains. In the field of neural networks, feature selection has been used in many applications and their methods have been employed. In this study we present neural network approaches … …Journal of Computer Science, Vol. 8, Issue 4 · 2 Feb 2012 · 6,840 accessesView PDFCite
Research ArticleOpen accessIn the abstractMedical Image Classification Using Genetic Optimized Elman NetworkT. Baranidharan, D. K. GhoshProblem statement: Advancements in the internet and digital images have resulted in a huge database of images. Most of the current search engines found in the web depends only on images that can be retrieved using metadata, which generates a lot of unwanted results in the results got. Content-Based Image Retrieval (CBIR) system is the utilization of computer vision techniques … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 7,717 accessesView PDFCite
Research ArticleOpen accessIn the abstractCerebrovascular Accident Attack Classification Using Multilayer Feed Forward Artificial Neural Network with Back Propagation ErrorOlatubosun Olabode, Bola Titilayo OlabodeProblem statement: Most important problems of medical diagnosis. When there is a cerebrovascular accident attach the chances of a successful treatment depends essentially on the early diagnosis. In practice the part of medical errors while diagnosing a stroke type comes to 20-45% even for experienced doctors and the scope of methods of neurovisualization at stroke diagnosis are limited. Approach: In … …Journal of Computer Science, Vol. 8, Issue 1 · 26 Oct 2011 · 7,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractContent Based Image Retrieval using Novel Gaussian Fuzzy Feed Forward-Neural NetworkC. Ramesh Babu Durai, V. DuraisamyProblem statement: With extensive digitization of images, diagrams and paintings, traditional keyword based search has been found to be inefficient for retrieval of the required data. Content-Based Image Retrieval (CBIR) system responds to image queries as input and relies on image content, using techniques from computer vision and image processing to interpret and understand it, while using techniques from information … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 7,326 accessesView PDFCite