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 ...

If you equate step aerobics with leg warmers and spandex, well, you’re not wrong—but you’re stuck in the 1980s version of it. As TikTok videos that have amassed millions of views show, the retro ...

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 ...

# Welcome to Course 4's first assignment! In this assignment, you will implement convolutional (CONV) and pooling (POOL) layers in numpy, including both forward propagation and (optionally) backward ...