A review on deep learning techniques for 3D sensed data classification
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Summary
The current state-of-the-art deep learning architectures for processing unstructured Euclidean data are reviewed including; RGB-D, multi-view, volumetric and fully end-to-end architecture designs.
- Type
- article
- Published
- 2019-06-25
- Cited by
- 179
- References
- 119
- Access
- Open access
- OpenAlex
- https://openalex.org/W2955472583
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:195874255
Keywords
Deep learning, Convolutional neural network, Scale (ratio), Range (aeronautics), Robotics
References
- SLOPE BASED FILTERING OF LASER ALTIMETRY DATA
- 3D URBAN GIS FROM LASER ALTIMETER AND 2D MAP DATA
- Unsupervised Visual Representation Learning by Context Prediction
- Learning to Segment Object Candidates
- Multimodal deep learning for robust RGB-D object recognition
- ViDRILO: The Visual and Depth Robot Indoor Localization with Objects information dataset
- You Only Look Once: Unified, Real-Time Object Detection
- Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration
- Multi-view Convolutional Neural Networks for 3D Shape Recognition
- Spectral Networks and Locally Connected Networks on Graphs
- Fully convolutional networks for semantic segmentation
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- SUN RGB-D: A RGB-D scene understanding benchmark suite
- Fast High‐Dimensional Filtering Using the Permutohedral Lattice
- Contextual classification of lidar data and building object detection in urban areas
- 3D free-form object recognition in range images using local surface patches
- SUN3D: A Database of Big Spaces Reconstructed Using SfM and Object Labels
- Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
- Intrinsic shape signatures: A shape descriptor for 3D object recognition
- Multiscale Combinatorial Grouping
Cited by
- SynthCity: A large scale synthetic point cloud
- Extracting Diameter at Breast Height with a Handheld Mobile LiDAR System in an Outdoor Environment
- Road Environment Semantic Segmentation with Deep Learning from MLS Point Cloud Data
- A MULTI-PURPOSE BENCHMARK FOR PHOTOGRAMMETRIC URBAN 3D RECONSTRUCTION IN A CONTROLLED ENVIRONMENT
- Deep Learning on Point Clouds and Its Application: A Survey
- AERIAL POINT CLOUD CLASSIFICATION WITH DEEP LEARNING AND MACHINE LEARNING ALGORITHMS
- Sensor Data Visualization for Indoor Point Clouds
- A Point-Wise LiDAR and Image Multimodal Fusion Network (PMNet) for Aerial Point Cloud 3D Semantic Segmentation
- Transfer Learning in urban object classification: Online images to recognize point clouds
- Multi-View Features Joint Learning with Label and Local Distribution Consistency for Point Cloud Classification
- Rotation invariant features based on three dimensional Gaussian Markov random fields for volumetric texture classification
- Geospatial Artificial Intelligence: Potentials of Machine Learning for 3D Point Clouds and Geospatial Digital Twins
- Classification of different vehicles in traffic using RGB and Depth images: A Fast RCNN Approach
- Quality Control of Neuron Reconstruction Based on Deep Learning
- A Review on Deep Learning Approaches for 3D Data Representations in Retrieval and Classifications
- Point Cloud Classification Model Based on a Dual-Input Deep Network Framework
- Deep Convolutional Neural Network Design Approach for 3D Object Detection for Robotic Grasping
- Finding Your (3D) Center: 3D Object Detection Using a Learned Loss
- VoroCNN: Deep convolutional neural network built on 3D Voronoi tessellation of protein structures
- A Plastic Contamination Image Dataset for Deep Learning Model Development and Training
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