A hierarchical approach for fine-grained urban villages recognition fusing remote and social sensing data

[1]  Exploring Spatio-Temporal Patterns of Urban Village Redevelopment: The Case of Shenzhen, China , 2021, Land.

[2]  Qingquan Li,et al.  Scale Effect on Fusing Remote Sensing and Human Sensing to Portray Urban Functions , 2021, IEEE Geoscience and Remote Sensing Letters.

[3]  Michael Wurm,et al.  Mapping urban villages using fully convolutional neural networks , 2020 .

[4]  Jiasong Zhu,et al.  Deep learning-based remote and social sensing data fusion for urban region function recognition , 2020 .

[5]  Yonggoo Kim,et al.  Evaluation of Two EGFR Mutation Tests on Tumor and Plasma from Patients with Non-Small Cell Lung Cancer , 2020, Cancers.

[6]  Guanghui Wang,et al.  MDFN: Multi-Scale Deep Feature Learning Network for Object Detection , 2019, Pattern Recognit..

[7]  Jie Chen,et al.  Urban Function Identification Based on POI and Taxi Trajectory Data , 2019, ICBDR.

[8]  Qingquan Li,et al.  Functional urban land use recognition integrating multi-source geospatial data and cross-correlations , 2019, Comput. Environ. Urban Syst..

[9]  Ying Liu,et al.  Unsupervised segmentation parameter selection using the local spatial statistics for remote sensing image segmentation , 2019, Int. J. Appl. Earth Obs. Geoinformation.

[10]  Vikrant Bhateja,et al.  Human visual system based optimized mathematical morphology approach for enhancement of brain MR images , 2019, Journal of Ambient Intelligence and Humanized Computing.

[11]  Zhe Zhu,et al.  Understanding an urbanizing planet: Strategic directions for remote sensing , 2019, Remote Sensing of Environment.

[12]  Qiang Chen,et al.  Multi-resolution segmentation parameters optimization and evaluation for VHR remote sensing image based on meanNSQI and discrepancy measure , 2019, Journal of Spatial Science.

[13]  Krithi Ramamritham,et al.  Transfer learning approach to map urban slums using high and medium resolution satellite imagery , 2019, Habitat International.

[14]  Xiao Xiang Zhu,et al.  Semantic segmentation of slums in satellite images using transfer learning on fully convolutional neural networks , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[15]  Sabine Vanhuysse,et al.  Fully Convolutional Networks and Geographic Object-Based Image Analysis for the Classification of VHR Imagery , 2019, Remote. Sens..

[16]  Shihong Du,et al.  Integrating bottom-up classification and top-down feedback for improving urban land-cover and functional-zone mapping , 2018, Remote Sensing of Environment.

[17]  Yao Yao,et al.  A time series of urban extent in China using DSMP/OLS nighttime light data , 2018, PloS one.

[18]  H. Taubenböck,et al.  The morphology of the Arrival City - A global categorization based on literature surveys and remotely sensed data , 2018 .

[19]  H. Taubenböck,et al.  The similar size of slums , 2018 .

[20]  Geoffrey J. Hay,et al.  Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities , 2018 .

[21]  Shasha Lu,et al.  Assessment on the urbanization strategy in China: Achievements, challenges and reflections , 2018 .

[22]  Shihong Du,et al.  Hierarchical semantic cognition for urban functional zones with VHR satellite images and POI data , 2017 .

[23]  Xin Huang,et al.  Unsupervised Deep Feature Learning for Urban Village Detection from High-Resolution Remote Sensing Images , 2017 .

[24]  Peng Dou,et al.  Dynamic monitoring of land-use/land-cover change and urban expansion in Shenzhen using Landsat imagery from 1988 to 2015 , 2017 .

[25]  Hannes Taubenböck,et al.  Slum mapping in polarimetric SAR data using spatial features , 2017 .

[26]  Jin Zhao,et al.  Superpixel-Based Multiple Local CNN for Panchromatic and Multispectral Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[27]  Monika Kuffer,et al.  Slums from Space - 15 Years of Slum Mapping Using Remote Sensing , 2016, Remote. Sens..

[28]  Monika Kuffer,et al.  Extraction of Slum Areas From VHR Imagery Using GLCM Variance , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[29]  Shihong Du,et al.  A Linear Dirichlet Mixture Model for decomposing scenes: Application to analyzing urban functional zonings , 2015 .

[30]  Yu Liu,et al.  Multi-focus image fusion with dense SIFT , 2015, Inf. Fusion.

[31]  Chaogui Kang,et al.  Social Sensing: A New Approach to Understanding Our Socioeconomic Environments , 2015 .

[32]  Hui Liu,et al.  Spatiotemporal Detection and Analysis of Urban Villages in Mega City Regions of China Using High-Resolution Remotely Sensed Imagery , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[33]  Thomas Blaschke,et al.  Geographic Object-Based Image Analysis – Towards a new paradigm , 2014, ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing.

[34]  Senén Barro,et al.  Do we need hundreds of classifiers to solve real world classification problems? , 2014, J. Mach. Learn. Res..

[35]  Camille Couprie,et al.  Learning Hierarchical Features for Scene Labeling , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[36]  S. Geertman,et al.  What Drives the Spatial Development of Urban Villages in China? , 2013 .

[37]  M. Njenga,et al.  Urban agriculture, social capital, and food security in the Kibera slums of Nairobi, Kenya , 2013 .

[38]  M. Seghier,et al.  The Neural Substrates and Timing of Top–Down Processes during Coarse-to-Fine Categorization of Visual Scenes: A Combined fMRI and ERP Study , 2010, Journal of Cognitive Neuroscience.

[39]  Michael Möller,et al.  An Adaptive IHS Pan-Sharpening Method , 2010, IEEE Geoscience and Remote Sensing Letters.

[40]  Kenan Handzic Is legalized land tenure necessary in slum upgrading? Learning from Rio's land tenure policies in the Favela Bairro Program , 2010 .

[41]  Yanglin Wang,et al.  Urbanization and informal development in China: Urban villages in Shenzhen , 2009 .

[42]  Xinhua Zhuang,et al.  Image Analysis Using Mathematical Morphology , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.