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Salient areas in natural scenes are generally regarded as the candidates of attention focus in human eyes, which is the key stage in object detection. In computer vision, many models have been proposed to simulate the behavior of eyes such as SaliencyToolBox (STB), Neuromorphic Vision Toolkit (NVT) and etc., but they demand high computational cost and their(More)
Salient areas in natural scenes are generally regarded as areas which the human eye will typically focus on, and finding these areas is the key step in object detection. In computer vision, many models have been proposed to simulate the behavior of eyes such as SaliencyToolBox (STB), Neuromorphic Vision Toolkit (NVT), and others, but they demand high(More)
We present a methodology for the automatic identification and delineation of germ-layer components in H&E stained images of teratomas derived from human and nonhuman primate embryonic stem cells. A knowledge and understanding of the biology of these cells may lead to advances in tissue regeneration and repair, the treatment of genetic and developmental(More)
As a component of low-level vision processing, saliency detection facilitates subsequent processing such as object detection or recognition. In this paper, we argue that a reasonable saliency detector should have the ability to: (1) Detect both small and large saliency regions. The size of salient regions vary greatly. When the salient region is large,(More)
In this paper, we develop a robust signal space separation (rSSS) algorithm for real-time magnetoencephalography (MEG) data processing. rSSS is based on the spatial signal space separation (SSS) method and it applies robust regression to automatically detect and remove bad MEG channels so that the results of SSS are not distorted. We extend the existing(More)
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