For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

It's been recognized for some time that Alzheimer's disease affects brain regions differently and that tau - a protein known ...

Understanding how the human brain represents the information picked up by the senses is a longstanding objective of ...

In computed tomography (CT) imaging, highly attenuated metallic implants often result in strong metal artifacts, which significantly compromise image quality and pose considerable challenges for ...

In this paper, we propose a novel 3D self-attention convolutional neural network for the LDCT denoising problem. Our 3D self-attention module leverages the 3D volume of CT images to capture a wide ...

An early study by Han et al. [5] used a deep convolutional neural network (CNN) model to synthesize CT from MRI with pretrained VGG weights as initialization, and their work proved that the DL-based ...

Keywords: medical images, convolutional neural network, object detection, semantic segmentation, analysis Citation: Yang R and Yu Y (2021) Artificial Convolutional Neural Network in Object Detection ...