Convolution Neural Network
Research of System for Correcting Exam Papers Based on Convolution Neural Network
... In this experiment, all the algorithms used the same training samples and test samples, without too much extraction feature and debugging model, so some conclusions about handwritten digit recognition algorithms in ...
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Research on image classification model based on deep convolution neural network
... trieval. Convolution neural network (CNN) is very inter- ested in machine learning and has excellent performance in hyperspectral image ...connected network and the label of each pixel vec- ...
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A Review on Lung Cancer Detection using Convolution Neural Network
... Convolutional Neural Networks for Lung Cancer Screening in Computed Tomography (CT) Scans [3] In this paper researcher detected whether the lung cancer is malignant or benign by using the Convolution ...
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A Convolution Neural Network for Classification of Indian Faces
... using Convolution neural ...the neural network. The processed data is passed to the convolution neural network according to which the weights matrix is ...for ...
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AUTOMATIC HUMAN EMOTION RECOGNITION MODEL USING CONVOLUTION NEURAL NETWORK
... Abstract- Facial expression recognition systems have attracted abundant analysis interest among the sphere of AI. Many established facial expression recognition (FER) systems apply standard machine learning to pull out ...
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ABSTRACT: In this analysis proposed and evaluated the convolution neural network designed for classification of
... A Convolution Neural Network (CNN) is a powerful machine learning technique from the field of deep learning. CNNs are trained using large collections of diverse images. From these large collections, ...
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Aircraft detection in remote sensing images based on saliency and convolution neural network
... deep convolution network based on region proposal for detection, there are many negative samples in the generated region proposal, which will affect the model detection precision and ...deep ...
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Application research of convolution neural network in image classification of icing monitoring in power grid
... of convolution neural network, this paper applies it to the detection of power network ...power network icing detection image based on convolution neural network is ...
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Defect Detection of Mobile Phone Surface Based on Convolution Neural Network
... Automatic surface defect detection of mobile phone in large scale needs to process high resolution images and handle various defects while achieving high accuracy rate. This study proposes a defect detection method based ...
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Face Recognition using Landmark Estimation and Convolution Neural Network
... We specifically chose the Facial Key Point Detection Kaggle technique, which enabled us to test a broad range of methods and neural net models to fix the location issue which is otherwise simple. Recognition of ...
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An Image Classification Algorithm Based on Multidomain Convolution Neural Network
... CNN network structure that connects multiple image domains at the same time, which can quickly learn the effective features of input ...feedforward network of each image domain is similar to the traditional ...
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Enhancing Multi Exposure Images Using Convolution Neural Network
... similar network to VDSR and adds batch normalization layers after convolutional layers, which achieves higher PSNR than traditional image denoising ...deep neural networks to reinforce low-light pictures. ...
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A LeNet Based Convolution Neural Network for Image Steganalysis on Multiclass Classification
... Layer. Convolution is a feature extraction method, which requires training through a large number of pictures and repeated training and learning to achieve the best effect of the convolved ...after ...
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Fake News Detection using Convolution Neural Network in Deep Learning
... Internet and Social media provides facilities to the users to access news information and this can be a double-edged sword with both pros and cons, every day huge massive amount of news is generated and manipulated in ...
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Multi Modal Iris Recognition System based on Convolution Neural Network
... Abstract: Iris is most promising bio-metric trait for identification or authentication. Iris consists of patterns that are unique and highly random in nature .The discriminative property of iris pattern has attracted ...
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A Review on Brain Tumor Segmentation and Its Area Calculation in Brain using MRI Images (Review Paper on Brain Tumor Segmentstion and Area Calculation in Java and Open-CV by Using K-Means Clustering and Convolution Neural Network)
... convolutional neural network (CNN, or ConvNet) is a type of feed-forward artificial neural network in which the connectivity pattern between its neurons is inspired by the organization of the ...
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Some Studies on Convolution Neural Network
... classical neural network for the purpose of recognition of coloured normalized MINST digit demands to be abnormally large ...the network (by just increasing the number of hidden layers and the number ...
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A Convolution Neural Network for Optical Character Recognition and Subsequent Machine Translation
... convolutional neural network, is that it faces its limitations while attempting to model the dependencies between words or sequence values separated by a large number of other words, ...
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ECG Arrhythmia Classification Using a Convolution Neural Network
... forward neural networks (FFN) [6], learning vector quantization (LVQ) [7,8], back propagation neural networks (BPNN) [9], and regression neural networks (RNN) ...
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CONVOLUTION NEURAL NETWORK (CNN) BASED OBJECT DETECTION IN OCEANOGRAPHIC IMAGERY
... the neural network (which is considered as the biological inspired classifier), the activation function defines the percentage of the action potential firing for the input neural nodes or ...the ...
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