Artificial neural network (ANN). Automatic speech recognition (ASR)
Retina Based Biometric Identification System using Artificial Neural Network
... The methodology consists of two sections one is testing part and the other one is training part .The same process is carried out in both the sections .In the training part the retinal samples are trained and stored in ...
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Osmotic Drying Rate Estimation for Dehydration of Beetroot Slices using Artificial Neural Network
... of neural network is in its training & algorithm suggested by Rumelhart [9] is popular in this ...using Artificial Neural Network [15] ...
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Artificial Neural Network
... Artificial neural networks (ANNs) are computational models inspired by an animal's central nervous system (in particular the brain) which is capable of machine learning as well as pattern ...recognition. ...
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Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming
... 86 Malaysia, due to the difficulty of sampling and the possibility for wading in the water in these areas. New mathematical modelling methods were used to improve the sensitivity and performance of prediction equations ...
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Using Artificial Neural Network Modeling in Forecasting Revenue: Case Study in National Insurance Company/Iraq
... using Artificial Neural Network based on the actual annual data of the insurance premi- ums revenue between the years 1970 to ...using Artificial Neural Network con- firmed to be ...
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Study of Artificial Neural Network
... An Artificial Neural Network (ANN) is a mathematical model that tries to simulate the structure and functionalities of biological neural ...every artificial neural network ...
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DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY USING ADAPTIVE BOOSTING AND ARTIFICIAL NEURAL NETWORK
... Abstract: The disorders identified with retina of the eye such as: Diabetic Retinopathy (DR), age-related Macular Degeneration (AMD), Glaucoma, etc. can cause visual impairments. The retinal fundus pictures of the ...
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Analysis of cardiovascular (cvd)/coronary heart diseases(chd) using artificial neural network (ann)
... Neural Network (ANN) is a very important research domain now a days. Artificial Neural Network , coupled with Data mining , is a very exciting field ...sector, Neural ...
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Prediction of prostate cancer by deep learning with multilayer artificial neural network
... in artificial intelligence are now being applied to various fields in society and ...A neural network simulates the pattern recognition capabilities of a biological ...multilayer artificial ...
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Disease Identification in Cotton Plants Using Spatial FCM & PNN Classifier
... regression, artificial neural network (back propagation neural network, generalized regression neural network) and support vector machine (SVM) was ...
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The Performance of Deep Learning Algorithms on Automatic Pulmonary Nodule Detection and Classification Tested on Di erent Datasets That Are Not Derived from LIDC-IDRI: A Systematic Review
... convolutional neural network (CNN), massive training artificial neural network (MTANN), and deep stacked denoising autoencoder extreme learning machine ...
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Text Recognition using Convolutional Neural Network: A Review
... in converting the old printed documents into a soft copy .This will be an android app which will take image and convert it into soft copy using OCR (Optical Character Recognition) principles and concepts. It will be more ...
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DeepFHR: intelligent prediction of fetal Acidemia using fetal heart rate signals based on convolutional neural network
... AI: Artificial Intelligence; ANN: Artificial Neural Network; AUC: Area under the ROC curve; CAD: Computer Aided Diagnosis; CNN: Convolutional neural network; CWT: Continuous ...
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ABSTRACT: Chaos and chaos control are new theories and new fields of nonlinear dynamics. Chaotic motion
... Artificial neural network has been proved to have the characteristics of arbitrary approximation to nonlinear ...Combining artificial neural network with chaotic system, some ...
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Applying ANN, ANFIS, and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO
... process. Artificial neural network has ability of tracing a nonlinear form relationship between input and output ...ability, artificial neural networks have widespread application in ...
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Neural Network Priority Use of BTS for Optimizing Telecommunications in Indonesia
... Abstract—Artificial Neural Network Backpropogation is used to measure the Utilization Priority of BTS (Base Transceiver Station) to Optimize Telecommunication in 3T Disadvantaged, Outermost, Inside ...
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Radio location of partial discharge sources : a support vector regression approach
... Abstract: Partial discharge (PD) can provide a useful forewarning of asset failure in electricity substations. A significant proportion of assets are susceptible to PD due to incipient weakness in their dielectrics. This ...
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Vol 5, No 1 (2013)
... A neural network (NN), in the case of artificial neurons called artificial neural network (ANN) or simulated neural network (SNN), is an interconnected group of ...
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Digital Synthetic Ripple Modulator (SRM) for DC-DC Converter
... the Artificial Neural network (ANN) methodology to control the output voltage of a dc- dc buck converters and also the Artificial Neural network (ANN) methodology to control the ...
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A Survey Paper on Detection and Classification of Leaf Diseases in Plants
... are artificial neural network, Probabilistic Neural network, K means clustering for segmentation and GLCM and SGLDM for texture ...
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