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40 483 (0,343s)

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Hybrid Convolutional Neural Networks

The article proposes a new variant of convolutional neural networks - hybrid convolutional neural networks. This model of the network uses the 'winner-takes-all' principle and RBF-neurons...

BD - Teorie informace

  • 2008
  • D
Result

Deep Convolutional Neural Network for Fire Detection

Detection of smoke and fire using deep convolutional neural network to process video signals from camera.

Communication engineering and systems

  • 2020
  • D
  • Link
Result

The Use of Convolutional Neural Networks in Biomedical Data Processing

In this work, we study the use of convolutional neural networks for biomedical signal processing. Convolutional neural networks show promising results for classifying images when compared to tradi...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2017
  • D
  • Link
Result

Compression Artifacts Removal Using Convolutional Neural Networks

This paper shows that it is possible to train large and deep convolutional neural networks (CNN) for JPEG compression artifacts reduction....

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2016
  • JSC
  • Link
Result

Time Series Convolution Kernel Estimation

Main topics of the document: convolution kernel; time series; estimation; visualization; neural network...

Statistics and probability

  • 2018
  • D
  • Link
Result

Comparison of the Performance of Convolutional Neural Networks YOLOv5 and YOLOv8 for Application in Agricultural Technologies

Modern technologies with the potential to automate or greatly facilitate work are increasingly being applied in agriculture. In crop production, in particular, convolutional neural networks can assist in crop health monitor...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2023
  • D
  • Link
Result

Convolutional Neural Networks with Interpretable Kernels

We are focused on the theoretical background of convolutional neural networks. In particular, we examine the problem whether semantic meaning can be assigned to convolutional kernels in the first layers and how thi...

Applied mathematics

  • 2019
  • D
  • Link
Result

Fast blade shape optimization based on a neural-network-predicted flow field

. Convolution neural networks can significantly improve the speed of the optimization is to develop a convolution neural network which is able to predict flow fields in a blade cascade while satis...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2021
  • O
  • Link
Result

Pre-trained classifier of electrical motor winding fault based on multiple-branch convolutional neural networks

Software implementation of an artificial neural network for detecting a fault in the winding of an electric motor. The neural network is implemented in the Python environment in the Keras module designed for creati...

Robotics and automatic control

  • 2021
  • R
  • Link
Result

Hierarchical Discriminative Model for Spoken Language Understanding Based on Convolutional Neural Network

artificial neural networks. It is based on the existing work focused on the text classification using convolutional neural networks (CNNs). The presented method generalizes the convolutional laye...

Automation and control systems

  • 2015
  • D
  • Link
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