Classification of ALS Point Clouds Using End-to-End Deep Learning
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Norbert Pfeifer | Gottfried Mandlburger | Lukas Winiwarter | Stefan Schmohl | N. Pfeifer | G. Mandlburger | S. Schmohl | L. Winiwarter
[1] G. Lewicki,et al. Approximation by Superpositions of a Sigmoidal Function , 2003 .
[2] S. Schmohl,et al. SUBMANIFOLD SPARSE CONVOLUTIONAL NETWORKS FOR SEMANTIC SEGMENTATION OF LARGE-SCALE ALS POINT CLOUDS , 2019 .
[3] Michael Felsberg,et al. Deep Projective 3D Semantic Segmentation , 2017, CAIP.
[4] Silvio Savarese,et al. SEGCloud: Semantic Segmentation of 3D Point Clouds , 2017, 2017 International Conference on 3D Vision (3DV).
[5] Leonidas J. Guibas,et al. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Fabio Remondino,et al. A REVIEW OFPOINT CLOUDS SEGMENTATION AND CLASSIFICATION ALGORITHMS , 2017 .
[7] Jing Huang,et al. Point cloud labeling using 3D Convolutional Neural Network , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).
[8] Norbert Pfeifer,et al. Georeferenced Point Clouds: A Survey of Features and Point Cloud Management , 2013, ISPRS Int. J. Geo Inf..
[9] Monika Sester,et al. EXPLORING ALS AND DIM DATA FOR SEMANTIC SEGMENTATION USING CNNS , 2018, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.
[10] Konrad Schindler,et al. FAST SEMANTIC SEGMENTATION OF 3D POINT CLOUDS WITH STRONGLY VARYING DENSITY , 2016 .
[11] Alfred Stein,et al. Deep Fully Convolutional Networks for the Detection of Informal Settlements in VHR Images , 2017, IEEE Geoscience and Remote Sensing Letters.
[12] Uwe Soergel,et al. HIERARCHICAL HIGHER ORDER CRF FOR THE CLASSIFICATION OF AIRBORNE LIDAR POINT CLOUDS IN URBAN AREAS , 2016 .
[13] Clément Mallet. Analyse des données lidar aéroportées à Retour d'Onde Complète pour la cartographie des milieux urbains. (Analysis of Full-Waveform lidar data for urban area mapping) , 2010 .
[14] Wei Huang,et al. A Convolutional Neural Network-Based 3D Semantic Labeling Method for ALS Point Clouds , 2017, Remote. Sens..
[15] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[16] Alexandre Boulch,et al. Unstructured Point Cloud Semantic Labeling Using Deep Segmentation Networks , 2017, 3DOR@Eurographics.
[17] Ruibin Zhao,et al. Classifying airborne LiDAR point clouds via deep features learned by a multi-scale convolutional neural network , 2018, Int. J. Geogr. Inf. Sci..
[18] Leonidas J. Guibas,et al. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space , 2017, NIPS.
[19] Thomas A. Funkhouser,et al. Semantic Scene Completion from a Single Depth Image , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Matthias Nießner,et al. ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[22] Gregory Asner,et al. Spatially-Explicit Testing of a General Aboveground Carbon Density Estimation Model in a Western Amazonian Forest Using Airborne LiDAR , 2015, Remote. Sens..
[23] J. D. Wegner,et al. Large-scale supervised learning for 3D point cloud labeling: Semantic3d.net , 2018 .
[24] J. Niemeyer,et al. Contextual classification of lidar data and building object detection in urban areas , 2014 .
[25] D. Hubel,et al. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex , 1962, The Journal of physiology.
[26] Bernhard Höfle,et al. HELIOS: A MULTI-PURPOSE LIDAR SIMULATION FRAMEWORK FOR RESEARCH, PLANNING AND TRAINING OF LASER SCANNING OPERATIONS WITH AIRBORNE, GROUND-BASED MOBILE AND STATIONARY PLATFORMS , 2016 .
[27] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[28] Carl Salvaggio,et al. A Fully Convolutional Network for Semantic Labeling of 3D Point Clouds , 2017, ISPRS Journal of Photogrammetry and Remote Sensing.
[29] F ROSENBLATT,et al. The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.
[30] Norbert Pfeifer,et al. Classification of image matching point clouds over an urban area , 2018 .
[31] Martin Simonovsky,et al. Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[32] Johannes Heinzel,et al. Detecting Tree Stems from Volumetric TLS Data in Forest Environments with Rich Understory , 2016, Remote. Sens..
[33] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.
[34] Ronald M. Summers,et al. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning , 2016, IEEE Transactions on Medical Imaging.
[35] Matthias Nießner,et al. ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] S. J. Oude Elberink,et al. FULLY CONVOLUTIONAL NETWORKS FOR GROUND CLASSIFICATION FROM LIDAR POINT CLOUDS , 2018 .
[37] Martin Weinmann,et al. USING MULTI-SCALE FEATURES FOR THE 3D SEMANTIC LABELING OFAIRBORNE LASER SCANNING DATA , 2017 .
[38] C. Mallet,et al. AIRBORNE LIDAR FEATURE SELECTION FOR URBAN CLASSIFICATION USING RANDOM FORESTS , 2009 .
[39] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[40] Boris Jutzi,et al. Feature relevance assessment for the semantic interpretation of 3D point cloud data , 2013 .
[41] Wolfgang Wagner,et al. WAVEFORM ANALYSIS TECHNIQUES IN AIRBORNE LASER SCANNING , 2007 .
[42] Michael Cramer,et al. The DGPF-Test on Digital Airborne Camera Evaluation - Over- view and Test Design , 2010 .
[43] G. Vosselman. Point cloud segmentation for urban scene classification , 2013 .
[44] Xiangyun Hu,et al. Deep-Learning-Based Classification for DTM Extraction from ALS Point Cloud , 2016, Remote. Sens..
[45] W. Pitts,et al. A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.
[46] Stefan Hinz,et al. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers , 2015 .
[47] Roberto Cipolla,et al. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[48] Laurens van der Maaten,et al. 3D Semantic Segmentation with Submanifold Sparse Convolutional Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.