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603 results for “Neural”
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Research ArticleOpen accessEvery word in the titleAUTOMATIC MUSIC EMOTION CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK BASED ON VOCAL AND INSTRUMENTAL SOUND TIMBRESMudiana Binti Mokhsin, Nurlaila Binti Rosli, Suzana Zambri et al.Detecting emotion features in a song remains as a challenge in various area of research especially in Music Emotion Classification (MEC). In order to classify selected song with certain mood or emotion, the algorithms of the machine learning must be intelligent enough to learn the data features as to match the features accordingly to the accurate emotion. Until now, there … …Journal of Computer Science, Vol. 10, Issue 12 · 29 Dec 2014 · 8,527 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNEURAL CASCADED WITH FUZZY SCHEME FOR CONTROL OF A HYDROELECTRIC POWER PLANTA. Selwin Mich Priyadharson, T. Ramesh Kumar, M. S. Saravanan et al.A novel design for flow and level control in a hydroelectric power plant using Programmable Logic Controller (PLC)-Human Machine Interface (HMI) and neural cascaded with fuzzy scheme is proposed. This project will focus on design and development of flow and level controller for small scale hydro generating units by implementing gate control based on PLC-HMI with the proposed scheme. The … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 30 Sep 2014 · 6,527 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCLASSIFICATION OF DIGITAL IMAGES USING FUSION ELEVATED ORDER CLASSIFIER IN WAVELET NEURAL NETWORKR. Arulmurugan, P. SengottuvelanThe revival of wavelet neural networks obtained an extensive use in digital image processing. The shape representation, classification and detection play a very important role in the image analysis. Boosted Greedy Sparse Linear Discriminate Analysis (BGSLDA) trains the cascade level of detection in an efficient manner. With the application of reweighting concept and deployment of class-reparability criterion, lesser search was … …Journal of Computer Science, Vol. 10, Issue 9 · 23 Jun 2014 · 6,790 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIAY. S. Kumaraswamy, R. Ganesh KumarElectro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and … …Journal of Computer Science, Vol. 10, Issue 8 · 9 Apr 2014 · 6,968 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePREDICTION OF FIGHT OR FLIGHT RESPONSE USING ARTIFICIAL NEURAL NETWORKSAbhijit Suresh, Sai Swarna Latha, Pooja Nair, N. RadhikaThe modern society has posed several threats to the public. Public security is declining with increasing anti-social behaviour. Cases of rape and terrorist attacks have become increasingly common and there is a strong demand for a security system to control such modalities. Anti-social behaviour is a key issue of public concern. Public perceptions, however, have been improving recently. The vital … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 3 Apr 2014 · 8,041 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIMAGE SEGMENTATION WITH ARTIFICIAL NEURAL NETWORK FOR NUTRIENT DEFICIENCY IN COTTON CROPMaicon A. Sartin, Alexandre C.R. Da Silva, Claudinei KappesThe leaf analysis in a crop can present the need of a nutrient determined in the plant. The macronutrients deficiency in the cotton crop can be identified by specific type of colors variation by leaves images. Early identification of macronutrients deficiency can help in the growing suitable of the crop and reduce the use of agricultural inputs. This study investigates … …Journal of Computer Science, Vol. 10, Issue 6 · 4 Feb 2014 · 6,800 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA TIME-DELAY CASCADING NEURAL NETWORK ARCHITECTURE FOR MODELING TIME-DEPENDENT PREDICTOR IN ONSET PREDICTIONAgus Buono, Imas Sukaesih Sitanggang, Mushthofa, Aziz KustiyoThe occurrence of rain before the real start of a rainy season often mislead farmers into thinking that rainy season has started and suggesting them to start planting immediately. In reality, rainy season has not started yet, causing the already-planted rice seed to experience dehydration. Therefore, a model that can predict the onset of rainy season is required, so that … …Journal of Computer Science, Vol. 10, Issue 6 · 29 Jan 2014 · 6,647 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCONTENT BASED BATIK IMAGE CLASSIFICATION USING WAVELET TRANSFORM AND FUZZY NEURAL NETWORKAbdul Haris RangkutiIn this paper we introduce the content-based image classification using wavelet transform with Daubechies type 2 level 2 to process the characteristic texture consisting of standard deviation, mean and energy as Input variables, using the method of Fuzzy Neural Network (FNN). All the input value will be processed using fuzzyfication with 5 categories namely Very Low (VL), Low (L), Medium … …Journal of Computer Science, Vol. 10, Issue 4 · 19 Dec 2013 · 6,683 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleGENERALIZED REGRESSION NEURAL NETWORK BASED EXPERT SYSTEM FOR HEPATITIS B DIAGNOSISC. Mahesh, E. Kannan, M. S. SaravananHepatitis B is a potentially life-threatening liver infection caused by the hepatitis B virus. The virus interferes with the function of the liver while replicating in hepatocytes. It is a major global health problem and the most serious type of viral hepatitis. Chronic liver disease is caused by viral hepatitis and putting people at high risk of death from cirrhosis … …Journal of Computer Science, Vol. 10, Issue 4 · 3 Dec 2013 · 6,983 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHALF OF THRESHOLD ALGORITHM: AN ENHANCED LINEAR ADAPTIVE SKIPPING TRAINING ALGORITHM OR MULTILAYER FEEDFORWARD NEURAL NETWORKSManjula Devi Ramasamy, Kuppuswami Subbaraya GounderMultilayer Feed Forward Neural Network (MFNN) has been successfully administered architectures for solving a wide range of supervised pattern recognition tasks. The most problematic task of MFNN is training phase which consumes very long training time on very huge training datasets. An enhanced linear adaptive skipping training algorithm for MFNN called Half of Threshold (HOT) is proposed in this research … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 22 Nov 2013 · 7,016 accessesView PDFCite