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Title: GitHub - deepVector/geospatial-machine-learning: A curated list of resources focused on Machine Learning in Geospatial Data Science.

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Description: A curated list of resources focused on Machine Learning in Geospatial Data Science. - deepVector/geospatial-machine-learning

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A 2017 Guide to Semantic Segmentation with Deep Learninghttp://blog.qure.ai/notes/semantic-segmentation-deep-learning-review
Deeplab Image Semantic Segmentation Networkhttps://sthalles.github.io/deep_segmentation_network/
deeplab_v3https://github.com/anxiangSir/deeplab_v3
deeplab_v3: Tensorflow Implementation of the Semantic Segmentation DeepLab_V3 CNNhttps://github.com/sthalles/deeplab_v3
Deep learning for satellite imagery via image segmentationhttps://blog.deepsense.ai/deep-learning-for-satellite-imagery-via-image-segmentation/
Deep Learning for Semantic Segmentation of Aerial Imageryhttps://www.azavea.com/blog/2017/05/30/deep-learning-on-aerial-imagery/
fieldRNN: Temporal Vegetation Classification with Recurrent Neural Networkshttps://github.com/TUM-LMF/fieldRNN
forecastVeg: A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Healthhttps://github.com/JohnNay/forecastVeg
How to do Semantic Segmentation using Deep learninghttps://medium.com/nanonets/how-to-do-image-segmentation-using-deep-learning-c673cc5862ef
Kaggle Hackathon with Tensorflow - Satellite Image Classificationhttps://www.meetup.com/machine-learning-society-sd/events/236876160/
label-maker: Data Preparation for Satellite Machine Learninghttps://github.com/developmentseed/label-maker
Object Detection on SpaceNethttps://medium.com/the-downlinq/object-detection-on-spacenet-5e691961d257
Practical advice for analysis of large, complex data setshttp://www.unofficialgoogledatascience.com/2016/10/practical-advice-for-analysis-of-large.html
Rules of Machine Learning: Best Practices for ML Engineeringhttps://developers.google.com/machine-learning/rules-of-ml/
satellite-image-object-detection: YOLO/YOLOv2 inspired deep network for object detection on satellite images (Tensorflow, Numpy, Pandas)https://github.com/marcbelmont/satellite-image-object-detection
Satellite Image Segmentation: a Workflow with U-Nethttps://vooban.com/en/tips-articles-geek-stuff/satellite-image-segmentation-workflow-with-u-net/
semantic_segmentation_satellite_imagehttps://github.com/msahamed/semantic_segmentation_satellite_image
ssai-cnn: Semantic Segmentation for Aerial / Satellite Images with Convolutional Neural Networkshttps://github.com/mitmul/ssai-cnn
raster-vision: deep learning for aerial/satellite imageryhttps://github.com/azavea/raster-vision
Using Convolutional Neural Networks to detect features in satellite imageshttp://ataspinar.com/2017/12/04/using-convolutional-neural-networks-to-detect-features-in-sattelite-images/
WaterNet: A convolutional neural network that identifies water in satellite imageshttps://github.com/treigerm/WaterNet
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Dstl Satellite Imagery Feature Detectionhttps://www.kaggle.com/c/dstl-satellite-imagery-feature-detection
Defence Science and Technology Laboratory (Dstl)https://www.gov.uk/government/organisations/defence-science-and-technology-laboratory
DeepSat (SAT-6) Airborne Datasethttps://www.kaggle.com/crawford/deepsat-sat6
SAT-4 and SAT-6 airborne datasetshttp://csc.lsu.edu/~saikat/deepsat/
National Agriculture Imagery Program (NAIP) datasethttp://www.fsa.usda.gov/Internet/FSA_File/naip_2009_info_final.pdf
SpaceNethttps://registry.opendata.aws/spacenet/
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Caffe CNN-based classification of hyperspectral images on GPUhttp://dx.doi.org/10.1007/s11227-018-2300-2
Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the communityhttp://dx.doi.org/10.1117/1.JRS.11.042609
Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Datahttp://dx.doi.org/10.1109/LGRS.2017.2681128
Deep learning for visual understanding: A reviewhttp://dx.doi.org/10.1016/j.neucom.2015.09.116
Deep learning in remote sensing scene classification: a data augmentation enhanced convolutional neural network frameworkhttp://dx.doi.org/10.1080/15481603.2017.1323377
Multi-label Classification of Satellite Images with Deep Learninghttps://patch-diff.githubusercontent.com/deepVector/geospatial-machine-learning/blob/master/cs231n.stanford.edu/reports/2017/pdfs/908.pdf
Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Modelshttps://arxiv.org/abs/1708.01580
TensorFlow: A System for Large-Scale Machine Learninghttp://arxiv.org/abs/1605.08695
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Advances in Artificial Systems for Medicine and Educationhttp://dx.doi.org/10.1007/978-3-319-67349-3
Data processinghttp://www.cambridge.org/9780521669481
Deep Learning with Applications Using Pythonhttp://www.apress.com/9781484235157
Digital Signal Processing and Spectral Analysis for Scientistshttp://dx.doi.org/10.1007/978-3-319-25468-5
Hyperspectral Remote Sensing: Fundamentals and Practiceshttps://www.crcpress.com/9781138747173
Image Classificationhttp://dx.doi.org/10.4135/9780857021052
Image Processinghttp://dx.doi.org/10.1007/978-1-4842-3453-2_4
Image Processing and GIS for Remote Sensing: Techniques and Applicationshttp://dx.doi.org/10.1002/9781118724194
Mathematical Models for Remote Sensing Image Processinghttp://dx.doi.org/10.1007/978-3-319-66330-2
Machine Learning Applications for Earth Observation, Earth Observation Open Science and Innovationhttp://dx.doi.org/10.1007/978-3-319-65633-5_8
Principles of Applied Remote Sensinghttp://dx.doi.org/10.1007/978-3-319-22560-9
Pro Deep Learning with TensorFlowhttp://dx.doi.org/10.1007/978-1-4842-3096-1
Remote Sensing Digital Image Analysishttp://dx.doi.org/10.1007/978-3-642-30062-2
Remotely Sensed Data Characterization, Classification, and Accuracieshttps://www.crcpress.com/9781482217865
Remote Sensing Image Fusionhttps://www.crcpress.com/9781466587496
Remote Sensing Imageryhttp://dx.doi.org/10.1002/9781118899106
TensorFlow Machine Learning Cookbookhttps://www.packtpub.com/big-data-and-business-intelligence/tensorflow-machine-learning-cookbook
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Classification Modelshttps://www.udacity.com/course/classification-models--ud978
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Intro to Machine Learninghttps://www.udacity.com/course/intro-to-machine-learning--ud120
Learn TensorFlow and deep learning, without a Ph.Dhttps://cloud.google.com/blog/big-data/2017/01/learn-tensorflow-and-deep-learning-without-a-phd
Machine Learning Crash Course with TensorFlow APIshttps://developers.google.com/machine-learning/crash-course/
ML Practicum: Image Classificationhttps://developers.google.com/machine-learning/practica/image-classification/
Tensorflow for Deep Learning Researchhttp://web.stanford.edu/class/cs20si/index.html
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