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- W2793155736 endingPage "694" @default.
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- W2793155736 abstract "Abstract Recent advances in the field of computer vision can be attributed to the emergence of deep learning techniques, in particular convolutional neural networks. Neural networks, partially inspired by the brain's visual cortex, enable a computer to “learn” the most important features of the images it is shown in relation to a specific, specified task. Given sufficient data and time, (deep) convolutional neural networks offer more easily designed, more generalizable, and significantly more accurate end‐to‐end systems than is possible with previously employed computer vision techniques. This review paper seeks to provide an overview of deep learning in the field of computer vision with an emphasis on recent progress in tasks involving 3D visual data. Through a backdrop of the mammalian visual processing system, we hope to also provide inspiration for future advances in automated visual processing." @default.
- W2793155736 created "2018-03-29" @default.
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- W2793155736 date "2017-11-01" @default.
- W2793155736 modified "2023-10-12" @default.
- W2793155736 title "3D computer vision based on machine learning with deep neural networks: A review" @default.
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- W2793155736 doi "https://doi.org/10.1002/jsid.617" @default.
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