Jan 16, 2023 · Bibliographic details on Learning Convolutional Neural Networks in the Frequency Domain.

Apr 14, 2022 · by Hengyue Pan, et al. ... Convolutional neural network (CNN) has achieved impressive success in computer vision during the past few decades. As ...

This finding shows that the proposed architecture can improve the accuracy of the deep learning-based frequency- domain convolutional neural network model ...

We explore artificially constraining the frequency spectra of these filters and data, called band-limiting, during training. The frequency domain constraints ...

[31] further proposed C3D for generic spatio-temporal feature learning in large-scale dataset and outperforms 2D convolutional neural network, which demonstrate ...

Frequency domain learning can be achieved by transforming images from the spatial domain to the spectral domain by utilizing frequency filters to attenuate or ...

Abstract and Figures ; The benefit of frequency domain convolution is that convolutions are pointwise ; products of the images and kernels. As the kernels are ...

Convolutional neural networks (CNN) are increasingly used in many areas of computer vision. They are particularly attractive because of their ability to ...

Methods which provide useful insight into time domain features (Ellis et al., 2021d) extracted by CNNs for EEG involve training a CNN with filters in the first ...

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Posted: Jul 16, 2020