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On the basis of the above analysis we propose a representation method (point cloud to 2D grid) and architecture that results in much less parameters for the CNN�...
MORE FOR LESS: INSIGHTS INTO CONVOLUTIONAL NETS FOR 3D POINT CLOUD ... A commonly used alternate is to represent the 3D data as one or more 2D images obtained by�...
Paper Detail ; Paper Title: More for less: Insights into convolutional nets for 3D Point Cloud Recognition ; Authors: Usama Shafiq, Murtaza Taj, LUMS Syed Babar�...
Usama Shafiq, Murtaza Taj , Mohsen Ali: More for less: Insights into convolutional nets for 3D point cloud recognition. ICIP 2017: 1607-1611.
Oct 14, 2024We introduce the composite layer, a flexible and general alternative to the existing convolutional operators that process 3D point clouds. We�...
Our optimized convolutional neural network framework greatly improves the quality of point-cloud compression, and the work is highly scalable.
Nov 28, 2023Among diverse types of deep neural networks (DNNs), Convolutional Neural Network (CNN) is the most effective algorithm for computer vision.
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Mar 30, 2024Our proposition entails a comprehensive review, encapsulating diverse 3D CNN algorithms for the segmentation of medical image anomalies and organs.
Jun 11, 2019Shape-based. Recognition of 3D Point Clouds in Urban Environments. ... Multi- view Convolutional Neural Networks for 3D Shape Recognition.