Deep Neural Networks for Computer Vision

Sergey I. Nikolenko ()
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Sergey I. Nikolenko: Synthesis AI

Chapter Chapter 3 in Synthetic Data for Deep Learning, 2021, pp 59-95 from Springer

Abstract: Abstract Computer vision problems are related to the understanding of digital images, video, or similar inputs such as 3D point clouds, solving problems such as image classification, object detection, segmentation, 3D scene understanding, object tracking in videos, and many more. Neural approaches to computer vision were originally modeled after the visual cortex of mammals, but soon became a science of their own, with many architectures already developed and new ones appearing up to this day. In this chapter, we discuss the most popular architectures for computer vision, concentrating mainly on ideas rather than specific models. We also discuss the first step towards synthetic data for computer vision: data augmentation.

Date: 2021
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DOI: 10.1007/978-3-030-75178-4_3

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