MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

Abstract: SimpleConvolution is the most important and time-consuming part of convolutional neural networks (CNN) for image processing. Each slide of the window in two-dimensional convolution will ...

U-Net and its variants have been widely used in the field of image segmentation. In this paper, a lightweight multi-scale Ghost U-Net (MSGU-Net) network architecture is proposed. This can efficiently ...

Walking 10,000 steps a day has been the talk of the fitness town for a hot minute. With health benefits such as enhanced cardiovascular fitness, muscular strength and even reduced risk of dementia, it ...

Among the architecture redesign options mentioned, using efficient blocks, specifically depthwise separable convolutions, is probably the easiest to implement as a proof of concept (POC). Depthwise ...

In the modern era, there has been explosive growth in the demand for computing power for cognitive image and video processing. While convolutional neural networks offer improved performance for image ...

" - Example: $a^{[l]}_i$ denotes the $i^{th}$ entry of the activations in layer $l$, assuming this is a fully connected (FC) layer.\n", "- $n_H$, $n_W$ and $n_C ...