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298 results for “Neural Networks”
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Research ArticleOpen accessPhrase in the titleFuture Emoji Entry Prediction Using Neural NetworksHelen Wilfred Raj, Santhi BalachandranIn today’s world, textual data has made momentous progress in social media. The rise of digital communication via text has paved the way to emoji, a pictographically represented way of expressing emotions. In digital communication, Emoji gives a visual appeal to the text, which improves communication and new vistas of exchange and creativity. While emoji entry prediction based on text … …Journal of Computer Science, Vol. 16, Issue 2 · 10 Aug 2019 · 9,137 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Enhanced Training- Based Arabic Sign Language Virtual Interpreter Using Parallel Recurrent Neural NetworksMohamed A. AbdouIntelligent machine translation systems have a remarkable importance in integrating people with disabilities in community. Arabic to Arabic sign language systems are limited. Deep Learning (DL) was successfully applied to problems related to music information retrieval, image recognition and text recognition, but its use in sign language recognition is rare. This paper introduces an automatic virtual translation system from Arabic … …Journal of Computer Science, Vol. 14, Issue 2 · 20 Feb 2018 · 7,628 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleEstimating the Scouring Depth of Bridge Pier Using Self-Organizing Neural Networks (SOM)Abolfazl Rafat, Gholam Abbas Barani, Amineh NaseriScouring is caused as a result of erosion of river bed by water flow and materials carried by water. This research estimates the scouring depth using self-organizing neural network (SOM). The obtained findings were compared with findings of other models. It was found that self- organizing neural network (SOM) has higher correlation coefficient (0.98), compared to other methods. It was … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 4 · 27 Nov 2017 · 7,500 accessesView PDFCite
Research ArticleOpen accessPhrase 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
Research ArticleOpen accessPhrase in the titlePerformance of Multiple Linear Regression and Nonlinear Neural Networks and Fuzzy Logic Techniques in Modelling House PricesSiti Amri, Gurudeo Anand TularamHouse price prediction continues to be important for government agencies insurance companies and real estate industry. This study investigates the performance of house sales price models based on linear and non-linear approaches to study the effects of selected variables. Linear stepwise Multiple Regression (MR) and nonlinear models of Neural Network (NN) and Adaptive Neuro-Fuzzy (ANFIS) are developed and compared. The … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 18 Dec 2012 · 8,430 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleCross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural NetworksShirin A. Mojarad, Satnam S. Dlay, Wai L. Woo, Gajanan V. SherbetProblem statement: The presence of metastasis in the regional lymph nodes is the most important factor in predicting prognosis in breast cancer. Many biomarkers have been identified that appear to relate to the aggressive behaviour of cancer. However, the nonlinear relation of these markers to nodal status and also the existence of complex interaction between markers have prohibited an accurate … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 4 · 20 Feb 2012 · 7,699 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleImproved Application of Paraconsistent Artificial Neural Networks in Diagnosis of Alzheimer's DiseaseHelder F.S. Lopes, Jair M. Abe, Paulo A.M. Kanda et al.Problem statement: The visual analysis of Electroencephalogram (EEG) activity has shown useful as a complementary tool in Alzheimer Disease (AD diagnosis) when the diagnosis remains uncertain, in addition to be used in some clinical protocols. However, this analysis is subject to the inherent equipment imprecision, biological artifact, electrical records, and subjective physician interpretation of the visual analysis variation. The Artificial … …Neuroscience International, Vol. 2, Issue 1 · 6 Oct 2011 · 12,061 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleArtificial Neural Networks Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition SystemSaleh Mufleh Al-Saqer, Ghulam Mubashar HassanProblem statement: The most dangerous insect for the existence of palm trees in entire world is Red Palm Weevil (scientifically named as Rynchophorus Ferrugineous, Oliveir). The proposed research is conducted to develop an identification system for Automated Wireless Red Palm Weevil Detection and exterminated. The core idea of the proposed research is to develop software that can utilize image processing … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 3 · 4 Aug 2011 · 9,187 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePrediction of Sulfur Dioxide (SO2) Concentration Levels from the Mina Al-Fahal Refinery in Oman Using Artificial Neural NetworksSabah A. Abdul-Wahab, Saleh M. Al-AlawiIn this investigation, two Artificial Neural Network (ANN) models were applied for predicting ground-level sulfur dioxide (SO2) in the Sultanate of Oman in order to provide an early warning advisory for the protection of public health. The objective of the first model (Model I) was to use ANN to predict sulfur dioxide (SO2) levels at certain receptors from the Mina … …American Journal of Environmental Sciences, Vol. 4, Issue 5 · 31 Oct 2008 · 7,385 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFace Recognition using Eigenfaces and Neural NetworksMohamed Rizon, Muhammad Firdaus Hashim, Puteh Saad et al.In this study, we develop a computational model to identify the face of an unknown person’s by applying eigenfaces. The eigenfaces has been applied to extract the basic face of the human face images. The eigenfaces is then projecting onto human faces to identify unique features vectors. This significant features vector can be used to identify an unknown face by … …American Journal of Applied Sciences, Vol. 3, Issue 6 · 30 Jun 2006 · 6,940 accessesView PDFCite