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Comparison of Different Convolutional Neural Network Architectures for Satellite Image SegmentationConvolutional neural networks for detection geo-objects on the satellite images from DSTL, Landsat
Convolution Neural Network Learning Features for Handwritten Digit Recognition© 2020 IEEE. The classical six-layer neural network is considered. This network is used
Deep Neural Networks for Emotion Recognition methods. Deep convolutional neural networks and recurrent neural networks with bidirectional LSTM memory
Compressing a convolution neural network based on quantization. In this paper we experimentally investigate approaches to compression of convolutional neural network
Recognition of buildings on satellite images on practical: development of methods for solving the problem of determining structures on images using neural
Convolutional Neural Networks for Image Steganalysis computer vision problems. One of these models—Convolutional Neural Network—has been proven to be very
Application of Convolutional Neural Networks for Image Detection and Recognition Based on a Self-written Generator objects using convolutional neural networks is considered. The purpose of the work is to implement
Convolutional Neural Networks for Image Steganalysis computer vision problems. One of these models—Convolutional Neural Network—has been proven to be very
Combined Convolutional and Perceptron Neural Networks for Handwritten Digits Recognition© 2020 IEEE. The use of a combination of a convolutional neural network and multilayer perceptrons
Обнаружение объектов на изображении с использованием сверточных нейронных сетей of convolutional neural networks are considered. The layers that make up the convolutional neural network
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