Reducing the radiation dose leads to increased CT image noise and artifacts, which can adversely affect not only the radiologists judgement but also the performance of downstream medical image analysis tasks. Various low-dose CT denoising methods, especially the recent deep learning based approaches, ...
Autoencoders belong to the family of unsupervised learning techniques and represent models that are able to leverage the neural networks for the representation learning task, e.g., denoising, feature reduction, clustering, image processing [44,45,46,47,48,49]. Specifically, an autoencoder is a...
Autoencoders belong to the family of unsupervised learning techniques and represent models that are able to leverage the neural networks for the representation learning task, e.g., denoising, feature reduction, clustering, image processing [44,45,46,47,48,49]. Specifically, an autoencoder is a...
in aerial images using image processing and computer vision techniques, and has been widely used in many fields such as environmental monitoring, smart cites, military reconnaissance, etc. In recent years, the widespread application of deep learning techniques such as convolutional neural networks (CNN...