Exploring the Potential of Machine Learning for Automatic Slum Identification from VHR Imagery
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Exploring the Potential of Machine Learning for Automatic Slum Identification from VHR Imagery
Authors
Keywords
-
Journal
Remote Sensing
Volume 9, Issue 9, Pages 895
Publisher
MDPI AG
Online
2017-08-30
DOI
10.3390/rs9090895
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- The Use of Landscape Metrics and Transfer Learning to Explore Urban Villages in China
- (2017) Hui Liu et al. Remote Sensing
- Capturing the Diversity of Deprived Areas with Image-Based Features: The Case of Mumbai
- (2017) Monika Kuffer et al. Remote Sensing
- Determining the Relationship Between Census Data and Spatial Features Derived From High-Resolution Imagery in Accra, Ghana
- (2016) Avery Sandborn et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Extraction of Slum Areas From VHR Imagery Using GLCM Variance
- (2016) Monika Kuffer et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Urban slum detection using texture and spatial metrics derived from satellite imagery
- (2016) Divyani Kohli et al. Journal of Spatial Science
- Identification of Village Building via Google Earth Images and Supervised Machine Learning Methods
- (2016) Zhiling Guo et al. Remote Sensing
- Slums from Space—15 Years of Slum Mapping Using Remote Sensing
- (2016) Monika Kuffer et al. Remote Sensing
- An Improved Evaluation of Kolmogorov's Distribution
- (2015) Luis Carvalho Journal of Statistical Software
- Measuring intra-urban poverty using land cover and texture metrics derived from remote sensing data
- (2015) Juan C. Duque et al. LANDSCAPE AND URBAN PLANNING
- Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery
- (2013) Oleksandr Kit et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use/Cover Mapping
- (2013) Qiong Hu et al. Remote Sensing
- Using semivariogram indices to analyse heterogeneity in spatial patterns in remotely sensed images
- (2012) A. Balaguer-Beser et al. COMPUTERS & GEOSCIENCES
- A feature extraction software tool for agricultural object-based image analysis
- (2011) L.A. Ruiz et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deriving fine-scale socioeconomic information of urban areas using very high-resolution satellite imagery
- (2011) Francisco J. Tapiador et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification
- (2009) A. Balaguer et al. COMPUTERS & GEOSCIENCES
- Remote sensing application for property tax evaluation
- (2007) Sadhana Jain International Journal of Applied Earth Observation and Geoinformation
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search