Abstract: The existing infrared and visible image fusion methods typically apply small kernel convolution that can extract local information or details of the source images but cannot easily perceive ...
Abstract: Blind deconvolution is to recover a sharp version of a given blurry image or signal when the blur kernel is unknown. Because this problem is ill-conditioned in nature, effectual criteria ...
Researchers have developed a new artificial intelligence (AI) technique that brings machine vision closer to how the human brain processes images. Called Lp-Convolution, this method improves the ...
A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...
The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...
Hyperspectral images are a valuable tool for remotely sensing important characteristics of a variety of landscapes, including water quality and the status of marine disasters. However, hyperspectral ...
Three-dimensional (3D) liver tumor segmentation from Computed Tomography (CT) images is a prerequisite for computer-aided diagnosis, treatment planning, and monitoring of liver cancer. Despite many ...
The receptive field is defined as the region in the input space that a particular CNN’s feature is looking at (i.e. be affected by). For convolutional neural network, the number of output features in ...
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