This paper describes our approach to the DSTL Satellite Imagery Feature Detection challenge run by Kaggle. Optimization wise I used the Jaccard loss directly with Adam as optimizer (I did not get much improvement from NAdam). Well for land use land cover 13-15 zoom level is sufficient. Compare that to OneWeb, a SpaceX competitor, whose satellite constellation will orbit at 1,200 … One swarm measured 60 x 40 kilometres wide in the country’s northeast area, Intergovernmental Authority on Development (IGAD) said in a press release. 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. The colors in an image will depend on what kind of light the satellite instrument measured. One day for preprocessing, one day to train and predict, and another day to predict vehicles and generate submission. Once again, thank you to Dstl and Kaggle for hosting and organizing this terrific image segmentation competition — I believe this is by far the most exciting (and busy, due to the number of classes) competition I have had, and I am sure this is true for many others too. As Canvas Ventures VC Ben Narasin told us in his “AI in Industry” podcast interview, AI is secondary to the business model and goals of the company. Automating feature labeling will not only help Dstl make smart decisions more quickly around the defense and security of the UK, but also bring innovation to computer vision methodologies applied to satellite imagery. Tracks 5. The National Geospatial-Intelligence Agency (NGA) has offered a $50,000 prize pool for novel approaches that employ artificial intelligence to detect circular-shaped elements in satellite images. No augmentation with ensembling was performed on validation or test data. As part of the Circle Finder challenge NGA is looking for novel automated approaches to help detect, delineate and describe circular shaped features using satellite images. List of machine learning competitions for satellite imagery and remote sensing. Various widths (256x256, 288x288, etc.) Satellite Imagery Feature Detection using Deep Convolutional Neural Network: A Kaggle Competition. Oversampling on rare classes — oversampling was performed by sliding in smaller steps over positive frames and sliding in larger steps over negative frames than default window size. clock-data recovery, locked loops, high-speed I/O, etc. As part of the Circle Finder challenge NGA is looking for novel automated approaches to help detect, delineate and describe circular shaped features using satellite images. Satellite imagery is new to me, where can I start learning about it? U-NET training & ensembling with a variety of models that permuted bands and scales. (3)"Host" is the host(s) of the Competitions. Jul 26, 2018 Lava from Hawaii's Kilauea Volcano flowing to the Pacific Ocean, imaged July 25 by NASA's Advanced Spaceborne Thermal Emission and Reflection (ASTER) instrument. Get traffic statistics, SEO keyword opportunities, audience insights, and competitive analytics for Satellite-images. By MISSY FREDERICK Space News Staff Writer posted: 24 April 2006 12:07 pm ET My guess is that my vehicle and standing water scores (combined) were the ones that made a difference in this competition, since the other top competitors had either weak vehicle scores or weak standing water scores. Download PDF Abstract: This paper describes our approach to the DSTL Satellite Imagery Feature Detection challenge run by Kaggle. As primary data source RapidEye will operate an innovative space based geo-information system. "NGA mission success is contingent on a world-class workforce with a wide diversity of opinions and expertise,” NGA deputy director and 2020 Wash100 Award recipient Dr. Stacey Dixon. Authors: Vladimir Iglovikov, Sergey Mushinskiy, Vladimir Osin. Crops 7. Then I came across Kaggle’s State Farm Distracted Driver contest, which was a perfect fit. The other important classes which I spent a chunk of time on were the two vehicle classes. Our vast archive includes imagery from all leading providers, such as DigitalGlobe, Airbus, and Satrec Imaging. EXAMPLES OF SMALL VEHICLES RELATIVE TO ROADS AND BUILDINGS. The Worldview tool from NASA's Earth Observing System Data and Information System provides the capability to interactively browse over 900 global, full-resolution satellite imagery layers and then download the underlying data.Many of the imagery layers are updated daily and are available within three hours of observation - essentially showing the entire Earth as it looks "right now". For this competition, the number of true positives and false positives are aggregated over all of the test imagery and the F1 score is computed from the aggregated counts. Index methods for waterways — namely a combination of Non-Differential Water Index (NDWI) and Canopy Chlorophyl Content Index (CCCI). Slingshot Aerospace develops computer vision based solutions to extract intelligence and insights from ultra high-volume satellite, aerial and drone imagery to optimize decision making for … The same ground as you can see from Space, where can I learning! For standing water, one day for preprocessing, one day for preprocessing, one day for,... On developing the post and pre-processing flows strive to increase workforce opportunities for neurodiverse individuals scheme was applied on... Originally published at blog.kaggle.com on April 26, 2017 also have fixed the contour issue... ( s ) '' Host '' is the application of the art solution improved! 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