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367 results for “learning algorithm”
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Research ArticleOpen accessIn the abstractFall Detection Using the Histogram of Oriented Gradients and Decision-Based FusionMohamed Maher Ben Ismail, Arwa AlGabas, Ouiem BchirAs the number of fall incidents among elderly people and patients are continuously growing, researches boosted their researches to propose efficient automatic fall detection systems. In particular, they formulated the fall detection problem as a supervised learning task where some visual features are extracted from the video frames and used to automatically identify the position of a human as “Fall” … …Journal of Computer Science, Vol. 16, Issue 2 · 26 Feb 2020 · 7,505 accessesView PDFCite
Research ArticleOpen accessIn the abstractBIS-CATTLE: A Web Server for Breed Identification using Microsatellite DNA MarkersSarika Jaiswal, Sandeep Kumar Dhanda, M. A. Iquebal et al.Domestic cow, Bos taurus is one of the important species selected by humans for various traits, viz. milk yield, meat quality, draft ability, resistance to disease and pests and social and religious reasons. Since cattle domestication from Neolithic (8,000-10,000 years ago) today the population has reached 1.5 billion and further it’s likely to be 2.6 billion by 2050. High magnitude … …Current Research in Bioinformatics, Vol. 5, Issue 1 · 23 Jan 2016 · 9,317 accessesView PDFCite
Research ArticleOpen accessIn the abstractContent Based Image Retrieval of Ultrasound Liver Diseases Based on Hybrid ApproachR. Suganya, S. RajaramProblem statement: In the past few years, immense improvement was obtained in the field of Content-Based Image Retrieval (CBIR). Nevertheless, existing systems still fail when applied to medical image databases. Simple feature-extraction algorithms that operate on the entire image for characterization of color, texture, or shape cannot be related to the descriptive semantics of medical knowledge that is extracted from … …American Journal of Applied Sciences, Vol. 9, Issue 6 · 24 Mar 2012 · 7,648 accessesView PDFCite
Research ArticleOpen accessIn the abstractSteel Plates Faults Diagnosis with Data Mining ModelsMahmoud Fakhr, Alaa M. ElsayadProblem statement: Over the last two decades, Fault Diagnosis (FD) has a major importance to enhance the quality of manufacturing and to lessen the cost of product testing. Actually, quick and correct FD system helps to keep away from product quality problems and facilitates precautionary maintenance. FD may be considered as a pattern recognition problem. It has been gaining more … …Journal of Computer Science, Vol. 8, Issue 4 · 31 Jan 2012 · 11,383 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 · 7,335 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Efficient and Effective Immune Based ClassifierShahram Golzari, Shyamala Doraisamy, Md Nasir Sulaiman, Nur Izura UdzirProblem statement: Artificial Immune Recognition System (AIRS) is most popular and effective immune inspired classifier. Resource competition is one stage of AIRS. Resource competition is done based on the number of allocated resources. AIRS uses a linear method to allocate resources. The linear resource allocation increases the training time of classifier. Approach: In this study, a new nonlinear resource allocation … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,772 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvolution of Neural Controllers for Robot Navigation in Human EnvironmentsGenci Capi, Hideki TodaProblem statement: In this study, we presented a novel vision-based learning approach for autonomous robot navigation. Approach: In our method, we converted the captured image in a binary one, which after the partition is used as the input of the neural controller. Results: The neural control system, which maps the visual information to motor commands, is evolved online using real … …Journal of Computer Science, Vol. 6, Issue 8 · 31 Aug 2010 · 6,788 accessesView PDFCite
Research ArticleOpen accessIn the abstractChange Detection Using Neural Network with Improvement Factor in Satellite ImagesM. A. Fkirin, S. M. Badwai, Sayed A. MohamedProblem statement: The aim of this study is to investigate the applicability of using the neural network techniques in change detection of remotely sensed data. Approach: In addition, the tuning parameters of the network, such as encoding the output classes, adding the momentum term and learning rate, are investigated in order to achieve best network performance. Results: Neural network-based change … …American Journal of Environmental Sciences, Vol. 5, Issue 6 · 31 Dec 2009 · 6,650 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntrusion Preventing System using Intrusion Detection System Decision Tree Data MiningSyurahbil, Noraziah Ahmad, M. Fadly Zolkipli, Ahmed N. AbdallaProblem statement: To distinguish the activities of the network traffic that the intrusion and normal is very difficult and to need much time consuming. An analyst must review all the data that large and wide to find the sequence of intrusion on the network connection. Therefore, it needs a way that can detect network intrusion to reflect the current network … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 4 · 31 Dec 2009 · 7,341 accessesView PDFCite
Research ArticleOpen accessIn the abstractBoosting Kernel Discriminative Common Vectors for Face RecognitionC. Lakshmi, M. PonnavaikkoProblem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,579 accessesView PDFCite