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- W2890594912 abstract "We present ongoing work to harness biological approaches to achieving highly efficient egocentric perception by combining the space- variant imaging architecture of the mammalian retina with Deep Learn- ing methods. By pre-processing images collected by means of eye-tracking glasses to control the fixation locations of a software retina model, we demonstrate that we can reduce the input to a DCNN by a factor of 3, reduce the required number of training epochs and obtain over 98% clas- sification rates when training and validating the system on a database of over 26,000 images of 9 object classes." @default.
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- W2890594912 date "2018-09-09" @default.
- W2890594912 modified "2023-10-16" @default.
- W2890594912 title "Efficient Egocentric Visual Perception Combining Eye-tracking, a Software Retina and Deep Learning" @default.
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