Deep learning architectures for land cover classification using red and near-infrared satellite images
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[1] Jiangye Yuan,et al. Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[2] Haifeng Li,et al. RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data , 2017, ArXiv.
[3] Qi Tian,et al. Enhancing Micro-video Understanding by Harnessing External Sounds , 2017, ACM Multimedia.
[4] K. P. Soman,et al. Least Square Denoising in Spectral Domain for Hyperspectral Images , 2017 .
[5] V. Sowmya,et al. Dependency of Various Color and Intensity Planes on CNN Based Image Classification , 2017, SIRS.
[6] Qiuyan Yu,et al. Feasibility Study of Land Cover Classification Based on Normalized Difference Vegetation Index for Landslide Risk Assessment , 2016 .
[7] Qingshan Liu,et al. Learning Multiscale Deep Features for High-Resolution Satellite Image Scene Classification , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[8] Wei Liu,et al. Neural Compatibility Modeling with Attentive Knowledge Distillation , 2018, SIGIR.
[9] Bertrand Le Saux,et al. Segment-before-Detect: Vehicle Detection and Classification through Semantic Segmentation of Aerial Images , 2017, Remote. Sens..
[10] Nikolaos Doulamis,et al. Deep supervised learning for hyperspectral data classification through convolutional neural networks , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[11] Stefan Winkler,et al. Ground-based image analysis: A tutorial on machine-learning techniques and applications , 2016, IEEE Geoscience and Remote Sensing Magazine.
[12] V. Sowmya,et al. Aerial and Satellite Image Denoising using Least Square Weighted Regularization Method , 2016 .
[13] Yong Wang,et al. Assessing relationship of air quality index and vegetation type using hyperspectral remote sensing , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[14] V. Sowmya,et al. Least Square Based Fast Denoising Approach to Hyperspectral Imagery , 2016 .
[15] V. Sowmya,et al. Hyperspectral Image Denoising Using Legendre-Fenchel Transform for Improved Sparsity Based Classification , 2016 .
[16] Supratik Mukhopadhyay,et al. DeepSat: a learning framework for satellite imagery , 2015, SIGSPATIAL/GIS.
[17] S. Narayana Reddy,et al. Land cover classification based on NDVI using LANDSAT8 time series: A case study Tirupati region , 2016, 2016 International Conference on Communication and Signal Processing (ICCSP).
[18] Suvajit Dutta,et al. A comparative study of deep learning models for medical image classification , 2017 .
[19] Nilanjan Dey,et al. A survey of image classification methods and techniques , 2014, 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT).
[20] Jianshu Luo,et al. Analysis and Denoising of Hyperspectral Remote Sensing Image in the Curvelet Domain , 2013 .
[21] Qihao Weng,et al. A survey of image classification methods and techniques for improving classification performance , 2007 .
[22] Indranil Misra,et al. Kernel based learning approach for satellite image classification using support vector machine , 2011, 2011 IEEE Recent Advances in Intelligent Computational Systems.
[23] Yucel Cimtay,et al. Calculation of vegetation index for short wave infrared hyperspectral images , 2017, 2017 25th Signal Processing and Communications Applications Conference (SIU).
[24] Konstantinos Karantzalos,et al. BENCHMARKING DEEP LEARNING FRAMEWORKS FOR THE CLASSIFICATION OF VERY HIGH RESOLUTION SATELLITE MULTISPECTRAL DATA , 2016 .
[25] Thomas Hofmann,et al. Learning Aerial Image Segmentation From Online Maps , 2017, IEEE Transactions on Geoscience and Remote Sensing.
[26] Jun Ma,et al. NeuroStylist: Neural Compatibility Modeling for Clothing Matching , 2017, ACM Multimedia.
[27] Lior Bragilevsky,et al. Deep learning for Amazon satellite image analysis , 2017, 2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM).
[28] Jamie Sherrah,et al. Semantic Labeling of Aerial and Satellite Imagery , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[29] Chunmei Zhang,et al. Improving hyperspectral data classification of satellite imagery by using a sparse based new model with learning dictionary , 2014, 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).