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- W2372906948 abstract "The primate visual system efficiently and effectively solves a multitude of tasks from orientation discrimination to motion detection. Computer vision approaches to the same tasks often outperform biological visual systems. However, computer vision algorithms designed for a specific task rarely generalize to other tasks. Thus, integrating multiple computer vision algorithms to perform multiple tasks is a bulky and inelegant solution. The Computer Vision community is therefore beginning to implement algorithms that mimic the processing hierarchies present in the primate visual system in the hope of achieving more flexible and robust artificial vision systems [Kruger et al., 2013]. Here, we reappropriate the neuroscience “borrowed” by the Computer Vision community and ask whether neuromorphic computer vision solutions may give us insight into the functioning of the primate visual system. Specifically, we implement a neuromorphic algorithm for disparity estimation and compare its performance against that of human observers." @default.
- W2372906948 created "2016-06-24" @default.
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- W2372906948 date "2016-01-01" @default.
- W2372906948 modified "2023-09-27" @default.
- W2372906948 title "Can Neuromorphic Computer Vision Inform Vision Science? Disparity Estimation as a Case Study" @default.
- W2372906948 hasPublicationYear "2016" @default.
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