Review of multi-view 3D object recognition methods based on deep learning
Abstract Three-dimensional (3D) object recognition is widely used in automated driving,
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …
medical image analysis, virtual/augmented reality, artificial intelligence robots, and other …
Application of recurrent neural network to mechanical fault diagnosis: A review
J Zhu, Q Jiang, Y Shen, C Qian, F Xu, Q Zhu - Journal of Mechanical …, 2022 - Springer
With the development of intelligent manufacturing and automation, the precision and
complexity of mechanical equipment are increasing, which leads to a higher requirement for …
complexity of mechanical equipment are increasing, which leads to a higher requirement for …
Surface representation for point clouds
Most prior work represents the shapes of point clouds by coordinates. However, it is
insufficient to describe the local geometry directly. In this paper, we present RepSurf …
insufficient to describe the local geometry directly. In this paper, we present RepSurf …
Snowflakenet: Point cloud completion by snowflake point deconvolution with skip-transformer
Point cloud completion aims to predict a complete shape in high accuracy from its partial
observation. However, previous methods usually suffered from discrete nature of point cloud …
observation. However, previous methods usually suffered from discrete nature of point cloud …
Relation-shape convolutional neural network for point cloud analysis
Point cloud analysis is very challenging, as the shape implied in irregular points is difficult to
capture. In this paper, we propose RS-CNN, namely, Relation-Shape Convolutional Neural …
capture. In this paper, we propose RS-CNN, namely, Relation-Shape Convolutional Neural …
CNN-RNN based intelligent recommendation for online medical pre-diagnosis support
The rapidly developed Health 2.0 technology has provided people with more opportunities
to conduct online medical consultation than ever before. Understanding contexts within …
to conduct online medical consultation than ever before. Understanding contexts within …
View-GCN: View-based graph convolutional network for 3D shape analysis
View-based approach that recognizes 3D shape through its projected 2D images has
achieved state-of-the-art results for 3D shape recognition. The major challenge for view …
achieved state-of-the-art results for 3D shape recognition. The major challenge for view …
Pmp-net++: Point cloud completion by transformer-enhanced multi-step point moving paths
Point cloud completion concerns to predict missing part for incomplete 3D shapes. A
common strategy is to generate complete shape according to incomplete input. However …
common strategy is to generate complete shape according to incomplete input. However …
Pmp-net: Point cloud completion by learning multi-step point moving paths
The task of point cloud completion aims to predict the missing part for an incomplete 3D
shape. A widely used strategy is to generate a complete point cloud from the incomplete …
shape. A widely used strategy is to generate a complete point cloud from the incomplete …
Point cloud completion by skip-attention network with hierarchical folding
Point cloud completion aims to infer the complete geometries for missing regions of 3D
objects from incomplete ones. Previous methods usually predict the complete point cloud …
objects from incomplete ones. Previous methods usually predict the complete point cloud …