Data‐driven polyline simplification using a stacked autoencoder‐based deep neural network
出版年份 2022 全文链接
标题
Data‐driven polyline simplification using a stacked autoencoder‐based deep neural network
作者
关键词
-
出版物
Transactions in GIS
Volume 26, Issue 5, Pages 2302-2325
出版商
Wiley
发表日期
2022-06-16
DOI
10.1111/tgis.12965
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Filling gaps of cartographic polylines by using an encoder–decoder model
- (2022) Wenhao Yu et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- A hybrid approach to building simplification with an evaluator from a backpropagation neural network
- (2021) Min Yang et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- A multi-scale representation model of polyline based on head/tail breaks
- (2020) Pengcheng Liu et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Graph convolutional autoencoder model for the shape coding and cognition of buildings in maps
- (2020) Xiongfeng Yan et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Exploring the Potential of Deep Learning Segmentation for Mountain Roads Generalisation
- (2020) Azelle Courtial et al. ISPRS International Journal of Geo-Information
- Spatial interpolation using conditional generative adversarial neural networks
- (2019) Di Zhu et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Learning Cartographic Building Generalization with Deep Convolutional Neural Networks
- (2019) Yu Feng et al. ISPRS International Journal of Geo-Information
- GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond
- (2019) Krzysztof Janowicz et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Classifying airborne LiDAR point clouds via deep features learned by a multi-scale convolutional neural network
- (2018) Ruibin Zhao et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery
- (2018) Bo Huang et al. REMOTE SENSING OF ENVIRONMENT
- Building simplification using backpropagation neural networks: a combination of cartographers' expertise and raster-based local perception
- (2018) Boyan Cheng et al. GIScience & Remote Sensing
- Using multi-scale and hierarchical deep convolutional features for 3D semantic classification of TLS point clouds
- (2018) Zhou Guo et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- Envelope generation and simplification of polylines using Delaunay triangulation
- (2016) Tinghua Ai et al. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
- A New Simplification Approach Based on the Oblique-Dividing-Curve Method for Contour Lines
- (2016) Haizhong Qian et al. ISPRS International Journal of Geo-Information
- SimpliFly: A Methodology for Simplification and Thematic Enhancement of Trajectories
- (2015) Katerina Vrotsou et al. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
- Deep learning
- (2015) Yann LeCun et al. NATURE
- A Simplification of Ria Coastline with Geomorphologic Characteristics Preserved
- (2014) Tinghua Ai et al. MARINE GEODESY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now