neural network classification model
Plant classification based on leaf Shape features using Neural Network
... features classification of the 220 plants are ...artificial neural network classification method. Feed forward neural network classification model is designed to ...
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Intelligent Neural Network For Bacteria Classification: An Innovation In Artificial Neural Network
... The performance of INN was finally compared with the conventional ANN having same set of features of the bacterial species taken into consideration in this research work. The conventional ANN was trained as the same way ...
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An Optimal Deep Neural Network Model For Lymph Disease Identification And Classification
... and classification model. An optimal deep neural network (DNN) model is applied to classify the lymph data utilizing the stacked autoencoders (SA) which is generally used to extract the ...
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NeuroSVM: A Graphical User Interface for Identification of Liver Patients
... Accurate classification techniques are required for automatic identification of disease ...for classification of liver patients from healthy ...for classification using R ...of classification ...
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Classification and Forecasting of Bollywood Movies by Commercial Success using Back Propagation Neural Network model
... The decision makers of the Bollywood film industry could find out how much different specific scores of independent variables could be important to the commercial success of a film they are interested in producing with ...
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A Generative Attentional Neural Network Model for Dialogue Act Classification
... attention model is that the final hidden state is a function of all the inputs, hence it is usually more “infor- mative” than the earlier hidden states due to se- mantic accumulation (Wang et ...DA ...
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Implementation of hybrid classification model in distributed systems for network monitoring
... Machine) classification algorithm and Neural Networks classification algorithms identify the pitfalls and propose a new hybrid classification algorithm which is reliable, fast, efficient and ...
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Identification Of Weeds From Crops Using Convolutional Neural Network
... of network Architecture YannLeCun uses a new architecture which is good at object recognition in image dataset called the Convolutional Neural Network ...and model size and the model ...
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Winning Prediction Analysis in One-Day-International (ODI) Cricket Using Machine Learning Techniques
... a Neural Network based framework for semantic events detection in soccer ...Markov model is used to detect the play and break events from soccer ...multi model analysis and ability of ...
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Application research of convolution neural network in image classification of icing monitoring in power grid
... the network is still very complex, and the training is still very ...the network and reduce the complexity and over-fitting degree of the model, a pooling layer is usually followed by a convolution ...
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An Ensemble Classification Approach for Intrusion Detection
... ensemble classification method is proposed from different ...artificial neural network and random forest are used for ...Ensemble model is formed for producing better result. The model ...
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Multimodal Decision level Group Sentiment Prediction of Students in Classrooms
... Convolutional Neural Network (CNN) model trained on the FER2013 facial images database to generate the feature vector for classification of video-based ...Recurrent Neural ...
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Video Classification with Recurrent Neural Network
... CNN model for action recognition with novel 3D CNN model used for action ...This model extracts features from both the spatial and the temporal dimensions by performing 3D convolutions, thereby ...
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Research on image classification model based on deep convolution neural network
... CNN classification confidence design, reflect the usual complementary patterns of each ...convolutional neural network (CNN) and Naive Bayes data fusion scheme (called NB-CNN), which can be used to ...
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A Neural Network Approach for ECG Classification
... artificial neural networks (ANNs) can be regarded as an extension of many conventional or not, techniques ...[4]. Neural networks are adaptive machines which have „a natural propensity for storing ...
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Prediction of Heart Disease using RNN Algorithm
... authors applied ANN on two distinctive breast malignancy dataset. Both of these datasets utilizes the morph metric attributes. An enhanced ANN model [30] has been utilized. Back propagation has been utilized to ...
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Neural Network Based Model Predictive Control of Batch Extractive Distillation Process for Improving Purity of Acetone
... For the set point tracking case, each controller is applied to track the acetone distillate composition at the desired profile. Figures 7, 8 and 9 show the acetone distillate composition using NNMPC, NNDIC and PID ...
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Protection and Controlling of Transmission Lines by using Machine Learning Techinique
... facility network, right from generation through transmission to distribution ...grid network for cover of conductor, generator protection, motor protection, real time fault location, protection of bus bar ...
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Framework for a Genetic-Neuro-Fuzzy Inferential System for Diagnosis of Diabetes Mellitus
... modern society is diabetes mellitus and it is not only a medical problem but also a socio-economy. Artificial Intelligence techniques have been successfully employed in diabetes disease diagnosis, risk evaluation, ...
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Artificial Neural Network Classification for Gunshot Detection and Localization System
... window on top of the signal at time zero and truncates the signal within the window. After this, the SFFT of the truncated signal is computed and the process is continually repeated by incrementally sliding the window to ...
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