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3D convolutional neural network for object recognition: a review
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Journal Article
3D convolutional neural network for object recognition: a review
2019
Overview
Recognition of an object from an image or image sequences is an important task in computer vision. It is an important low-level image processing operation and plays a crucial role in many real-world applications. The challenges involved in object recognition are multi-model, multi-pose, complicated background, and depth variations. Recently developed methods have dealt with these challenges and have reported remarkable results for 3D objects. In this paper, a comprehensive overview of recent advances in 3D object recognition using Convolutional Neural Networks (CNN) has been presented. Along with the latest progress in 3D images, general overview of object recognition of 2D, 2.5D, and 3D images is presented.
Publisher
Springer Nature B.V
