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Search results for: neural network
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Year: 2013, Volume: 13, Number: 1
... An Effect of Noise in Printed Character Recognition System Using Neural Network Sandel GHEORGHITA1, Radu MUNTEANU1, Adrian GRAUR2 ... obtained at the outputs of each network are The neural networks are architectures that use several processed by using analysis ... designed for this layers with interconnected neurons. The standard neuron has purpose. The suggested model is made up ...
Year: 2013, Volume: 13, Number: 1
... 2013 Segmentation of Bone Structure in X-ray Images using Convolutional Neural Network Cosmin CERNAZANU-GLAVAN, Stefan HOLBAN Politehnica University of ... presented for the first time by present, the convolutional networks are the best techniques for Fukushima [1] ... 1980) by using a network architecture image segmentation. This fact is demonstrated by their wide (Neocognitron) ...
Year: 2022, Volume: 22, Number: 1
... within the dataset is very ï‚· The success of Recurrent Neural Networks (RNN) in similar to normal traffic ... A Hybrid Deep Learning Approach for Intrusion Detection in IoT Networks Murat EMEÇ, Mehmet Hilal Ã-ZCANHAN Department of Computer ... . With increasing mission- every IoT device on the network. Therefore, IoT devices are critical IoT data ...
Year: 2019, Volume: 19, Number: 2
... A Diagonally Weighted Binary Memristor Crossbar Architecture Based on Multilayer Neural Network for Better Accuracy Rate in Speech Recognition Application ... by Hewlett-Packard lab and completely made based on multilayer neural networks is proposed in the speech in 2008, has ... a new research field in applying the recognition application. Here, the memristor crossbar circuit memristor device to neuron ...
Year: 2023, Volume: 23, Number: 2
... examines classes of epilepsy. the performance of the convolutional neural network (CNN) In general, two tasks ... a dataset of features extracted from the EEG convolutional neural networks and support vector machines. signal, and the ... is trained with a dataset of Scalogram In addition, efficient heuristics for selecting electrodes are images from the EEG ...
36. Transfer Learning Based Convolutional Neural Network for Classification of Remote Sensing Images
Year: 2023, Volume: 23, Number: 4
... 23, Number 4, 2023 Transfer Learning Based Convolutional Neural Network for Classification of Remote Sensing Images Meena Prakash ... are shown monitoring etc., Presently, Convolutional Neural Networks in Fig. 1. (CNN) which ... deep learning based methods are successfully employed for classification problems due to its flexible Machine learning is concerned with mapping ...
Year: 2017, Volume: 17, Number: 3
... contains a USB interfaced multichannel learning methods such as Artificial Neural Networks (ANN) data acquisition (DAQ) ... and a graphical user interfaced [1 ], [2 ], [7-9], decision trees ( ... are many powerful automatic power quality technique combined with neural network model to build the detection and recognition systems developed ...
Year: 2007, Volume: 7, Issue: 1
... . Autonomous Adaptive Control Method//Optical Memory and Neural [14] Nesteruk G. Ph., ... Kupriyanov M. C. (2003) Neural-fuzzy systems Network, Vol. 9, No 2,- ... ), Number 1 (27), 2007 Adaptive Networks Safety Control on Fuzzy Logic Vadim MUKHIN1, Elena ...
Year: 2018, Volume: 18, Number: 3
... Engineering Volume 18, Number 3, 2018 Pulse Coupled Neural Network based Near- Duplicate Detection of Images ( ... copyright protection, feature extraction, image processing, neural networks. I. INTRODUCTION a) Original Image b ... ND Image In this modern era, exposures to social network and in Figure 1. Example of ND Image ...
Year: 2020, Volume: 20, Number: 2
... The ARIMA is widely Machine (SVM), Autoregressive Neural Network, LSTM, used because of its simplicity ... a prediction model for the models such as artificial neural networks (ANNs) have been activities of companies [ ... ] using the exponential proposed [10]. The ANNs can be used to predict the next correction, ...
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