Jan 29, 2024 · This paper proposes a novel Element-wise Multiplication Layer (EML) to replace convolution layers, which can be trained in the frequency domain.

Nov 20, 2023 · A method based on frequency segmentation is proposed based on the energy distribution of wind turbine blades in different frequency bands.

Mar 4, 2024 · This essay delves into the multifaceted impact of Fourier Transform applications in CNNs, exploring its potential to drive future developments in the field.

Nov 21, 2023 · This paper proposes a noise-robust and accurate bearing fault diagnosis model based on time-frequency multi-domain 1D convolutional neural networks (CNNs) ...

Mar 10, 2024 · Large kernel convolutions are already implemented in Fourier domain, in all common frameworks. It's not an ML thing. For small-ish kernels (<15 typically?)

Sep 22, 2024 · We propose several novel CV-CNN-based models equipped with complex-valued attention gates for image denoising and super-resolution in the frequency domains.

Jan 15, 2024 · In this article, an interpretable time-frequency convolutional (TFconv) layer is proposed to extract fault-related time-frequency information.

Jan 2, 2024 · The Fourier Transform is a mathematical operation that transforms a signal from its original domain (usually time or space) to the frequency domain.

Nov 29, 2023 · This article develops a new method for interpreting CNN in bearing fault diagnosis from a time–frequency domain perspective.

Oct 6, 2024 · Abstract. It has been demonstrated that networks' parameters can be signifi- cantly reduced in the frequency domain with a very small decrease in accuracy.