Abstract: Point cloud analytics is poised to become a key workload on battery-powered embedded and mobile platforms in a wide range of emerging application domains, such as autonomous driving, ...
This is the tutorial bundle from Oracle Java SE tutorial homepage, last updated at 2021-2-10. The only modification is that I added this readme file. Publishing this repo as the download process from ...
Abstract: Recently, point cloud processing is becoming popular in AI-driven areas as 3D scanners are developing rapidly. However, this kind of data can have a massive file size, causing significant ...
Abstract: Change Point Detection (CPD) aims to identify moments of abrupt distribution shifts in data streams. Real-world high-dimensional CPD remains challenging due to data pattern complexity and ...
Abstract: In this paper, a Backward Attentive Fusing Network with Local Aggregation Classifier (BAF-LAC) is proposed to improve the performance of 3D point cloud semantic segmentation. It consists of ...
Abstract: Point cloud classification is highly dependent on how points' features are extracted and aggregated. The graph-based feature extraction strategies are currently used. Not only point ...
Abstract: Point cloud compression is critical to deploy 3D applications like autonomous driving. However, LiDAR point clouds contain many disconnected regions, where redundant bits for unoccupied 3D ...
Abstract: In spite of the good performance of convolutional neural network (CNN) and graph neural network (GNN) in 3D point cloud classification and segmentation at present, to aggregate local ...
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