neural network learning method
The Impact of the Neural Network Structure by the Detection of Undesirable Network Packets
... to neural network ...feed-forward neural network learning method with back-error ...of neural network provides sufficient flexibility and applicability to a wide ...
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A Convolution Neural Network Based Deep Learning System for Brain Tumor Detection towards MRI Image Segmentation
... Gaussian method uses cumulative region based segmentation method where the expected tumor region is marked out ...segmentation method. It is also classified as a pixel-based image segmentation ...
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Human-level Moving Object Recognition from Traffic Video
... Deep learning provides us an effective way to understand big data with a ...optimization method to determine the most compact region that contain the moving object, is ...deep neural network ...
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REVIEW PAPER ON AN IMPROVED APPROACH FOR BUSINESS AND MARKET INTELLIGENCE USING ARTIFICIAL NEURAL NETWORK
... is neural network. In this, neural networks technique is applied to get the predicted ...Although neural networks may have complex structure, long training time, and uneasily understandable ...
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Application of Neural Network to Game Algorithm
... of learning of neural network, and the establishment of the game algorithm of neural net- work was also ...game method on neural network is a powerful tool to solve the ...
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A Study of a Robotic Assembly System as a Collaborative Multi-Agent Organization
... recognition network, the problem-solving strategy and the learning ...solving, learning and communication. The system employs the reinforcement learning method for acquiring new ...
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An Unsupervised Learning Method for an Attacker Agent in Robot Soccer Competitions Based on the Kohonen Neural Network
... Reinforcement Learning (RL) as a common method in this domain because of its trial-and-error nature does not have great performance in using transcendental ...this method is limited to complex ...
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Deep Learning Based Crime Investigation Framework
... Deep learning has emerged as the best way to infer knowledge from data with more meaning and ...Deep Neural Networks in a variety of domains have made it an important area of ...Deep Neural Networks ...
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A Hybrid Machine Learning Method for Intrusion Detection
... forward neural network and support vector machine have considered to be the major techniques for data ...forward neural networks and it could overcome the mentioned ...sub network of several ...
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Research on Face Detection based on Deep Learning
... convolution neural network model of the deep learning method, and designed the face detector based on the selective search strategy and the improved Alexnet convolution neural ...
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Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... “The method then calls for learning as much as one can about what the parts of the brain do (primarily the physiologist’s field), and relat- ing the behavior as far as possible to this knowledge (primarily ...
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YNUWB at SemEval 2019 Task 6: K max pooling CNN with average meta embedding for identifying offensive language
... of network hatred in Twitter data samples (Bur- nap and Williams, ...machine learning methods to obtain tagged data from different Twitter accounts in an inex- pensive way, and to learn the binary ...
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Artificial Neural Networks Based Oil Price Forecasting: A Decade Review of the Literature
... multiscale neural network learning paradigm based on empirical mode decomposition method to predict the WTI crude oil ...decomposition method consists on decomposing the original daily ...
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Emotion Recognition And Classification Using Eeg: A Review
... single method. In future one can combine traditional method with machine learning to get automatic artifact ...Machine learning techniques like LDA, kNN are simple to implement but the ...
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DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY USING ADAPTIVE BOOSTING AND ARTIFICIAL NEURAL NETWORK
... proposed method of classification based on area and perimeter of blood vessels and hemorrhages produced significant results ...Probabilistic Neural Network (PNN) and Support Vector Machine were used ...
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Extreme Learning Machine Weight Optimization using Particle Swarm Optimization to Identify Sugar Cane Disease
... artificial neural network method with the Extreme Learning Machine (ELM) model can solve the problem of sugar cane disease classification with multilevel and multilabel symptom data with an ...
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Neuro-Fuzzy Scheduler for the Control of Real Time Spherical Tank Process
... forward neural network, but the links in an ANFIS only indicate the flow direction of signals between nodes and no weights is associated with the ...
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Modal Learning in a Neural Network
... the neural networks can be divided into 3: results during training (TD), results from testing using Natural test data (ND) and results from testing using just Pure test data ...propagation network, with ...
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Prediction of Heart Disease using RNN Algorithm
... ellipsoid method was proposed to detect the multiclass cancer ...oversampling method avoids the duplication of the ...machine learning algorithms. These metrics method classified into Pearson ...
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Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning
... the 12 measurements of each eye of all five test subjects, were bundled into two groups: a group for central fixation (120 “eyes,” the “CF set”) and a group for paracentral fixation (480 “eyes,” the “para-CF set”). Data ...
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