remotesensing   408

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Twitter
Why ? Tropical and subtropical forests are home to much of Earth's biodiversity at the center of the…
remotesensing  from twitter_favs
4 weeks ago by rukku
Sensing Wildfire Smoke at the Street Level – A Sense of Aclima
See how data from the California Camp Fire helped build a more detailed picture of pollution at the hyperlocal level.
climatechange  remotesensing  ppt 
5 weeks ago by NiklasJordan
udacity/CarND-Semantic-Segmentation
In this project, you'll label the pixels of a road in images using a Fully Convolutional Network (FCN).
temple  capstone  remotesensing  python  keras  segmentation  udacity 
5 weeks ago by cschrader
Dstl Satellite Imagery Competition, 3rd Place Winners’ Interview: Vladimir & Sergey | No Free Hunch
In their satellite imagery competition, the Defence Science and Technology Laboratory (Dstl) challenged Kagglers to apply novel techniques to "train an eye in the sky". From December 2016 to March 2017, 419 teams competed in this image segmentation challenge to detect and label 10 classes of objects including waterways, vehicles, and buildings. In this winners' interview, Vladimir and Sergey provide detailed insight into their 3rd place solution
temple  capstone  remotesensing  python  keras  segmentation  dstl 
5 weeks ago by cschrader
Deep learning for satellite imagery via image segmentation | deepsense.ai
In the recent Kaggle competition Dstl Satellite Imagery Feature Detection our deepsense.ai team won 4th place among 419 teams. We applied a modified U-Net – an artificial neural network for image segmentation. In this blog post we wish to present our deep learning solution and share the lessons that we have learnt in the process with you.
temple  capstone  remotesensing  python  keras  segmentation  dstl 
5 weeks ago by cschrader
Satellite Image Segmentation: a Workflow with U-Net
In the past few months, I have worked on such an image classifier which goal is to precisely identify objects in satellite images. This was done by training a few U-Net Convolutional Neural Networks (one per category of object — class — to predict) with Keras and TensorFlow, using GPU servers in the cloud.
temple  capstone  remotesensing  python  keras  segmentation  dstl 
5 weeks ago by cschrader
How to do Semantic Segmentation using Deep learning
With the popularity of deep learning in recent years, many semantic segmentation problems are being tackled using deep architectures, most often Convolutional Neural Nets, which surpass other approaches by a large margin in terms of accuracy and efficiency.
temple  capstone  remotesensing  python  keras  segmentation  udacity  khanhnamle1994 
5 weeks ago by cschrader
eo-learn.sentinel-hub.com
This example dataset will help you get started with Remote Sensing data and analysis in the open-source framework of eo-learn.

To promote the use of eo-learn, we have decided to share a dataset of EOPatches for the whole region of Slovenia for the year 2017. This data can be used in remote sensing applications, such as land cover classification.
temple  capstone  deeplearning  tensorflow  keras  R  remotesensing  data  datasets 
5 weeks ago by cschrader
robmarkcole/satellite-image-deep-learning: Resources for performing deep learning on satellite imagery
This document primarily lists resources for performing deep learning (DL) on satellite imagery. To a lesser extent Machine learning (ML, e.g. random forests, stochastic gradient descent) are also discussed, as are classical image processing techniques
temple  capstone  deeplearning  tensorflow  keras  R  remotesensing  data  datasets 
5 weeks ago by cschrader
Where can I download training data (with labelled classes) for land cover/land use classification?
I am performing land cover land use classification using Sentinel 1 and Sentinel 2 data. Since, in Sentinel 1 (SAR) data, the classes cannot be differentiated visibly, I need a way to develop the training dataset with labelled classes. Is there any website available where training dataset is available? I have already download the Sentinel 1 and Sentinel 2 data from ESA Copernicus hub. Thank you
temple  capstone  deeplearning  tensorflow  keras  python  remotesensing  data  datasets 
5 weeks ago by cschrader
Build your First Deep Learning Neural Network Model using Keras in Python
basic aim is to predict customer churn for a certain bank i.e. which customer is going to leave this bank service. Dataset is small(for learning purpose) and contains 10000 rows with 14 columns. I am not explaining data in detail as dataset is self explanatory. You can download data from my drive
temple  capstone  deeplearning  tensorflow  keras  python  remotesensing  data 
5 weeks ago by cschrader

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