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Visual attention is a crucial indicator of the relative importance of objects in visual scenes to human viewers. In this paper, we propose an algorithm to extract objects which attract visual attention from videos. As human attention is naturally biased towards high level semantic objects in visual scenes, this information can be valuable to extract salient objects. The proposed algorithm extracts...
Convolutional deep neural nets have emerged as a highly effective approach for machine vision, but there are a number of open issues regarding training (e.g., a large number of model parameters to be learned, and a number of manually tuned algorithm parameters) and interpretation (e.g., geometric interpretations of neurons at various levels of the hierarchy). In this paper, our goal is to explore...
While spatial neglect most commonly occurs after right hemisphere lesions, damage to diverse areas within the right hemisphere may lead to neglect, possibly through different mechanisms. To identify potentially different causes of neglect, the visual information used (the ‘perceptual template’) in a cueing task was estimated with a novel technique known as ‘classification images’ for five normal observers...
This study is the first to report the benefits of spatial covert attention on contrast sensitivity in a wide range of spatial frequencies when a target alone was presented in the absence of a local post-mask. We used a peripheral precue (a small circle indicating the target location) to explore the effects of covert spatial attention on contrast sensitivity as assessed by orientation discrimination...
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