![]() This entry was posted in Flights and tagged NZ flight PICO APRS on Maby andy. Today, we are excited to announce a leadership transition of the SpaceNet project to Maxar. ![]() ![]() Goodbye PS-3, it has been an amazing journey! Maxar co-founded SpaceNet with IQT Labs’ CosmiQ Works five years ago to harness open-source innovations in emerging computer vision technology to accelerate complex analysis of satellite imagery. Last packet from the balloon before it went out of APRS range The little balloon made it to New Zealand! Store in a cool dry space - Net 50g - Made in Australia with local and imported ingredients. Last received APRS packet from Australia coast Indian fennel seeds, Chongqing Sichuan peppercorns, spices. SpaceNet is an initiative dedicated to accelerating open-source, artificial intelligence applied research for geospatial applications, specifically foundational mapping (i.e. TX frequency will switch to NZ APRS frequency 144.575Mhz once 160.0 longitude is crossed. If the balloon survives the next day it might be within range of New Zealand APRS stations around 12:00 UTC 17/3 Resident: London UK / Athens Greece / Melbourne Australia Language: English / Greek Current Position : Socially engaged Artist / Radio Artist / Sound Artist. !call=a%2FVK3YT-11&timerange=86400&tail=86400Įxpected to reach Sydney over night, then it will be out to sea. Total weight including battery and antenna is 13g. This project studied building footprints detection in satellite imagery, a baseline need for many organizations that can enable many types of analyses. Payload is an ultra-light APRS beacon transmitting 10mW on 145.175Mhz. Introduction Experimental Setup UNet Model Project Structure Instructions for Model Development Introduction. Total training and inference times are calculated based upon an AWS p3.PS-3 is a long range PICO balloon flight from Melbourne to Sydney, release at 5:30pm AEST 16 March 2014 The SpaceNet Dataset is hosted as an Amazon Web Services (AWS) Public Dataset. Spacenet was headquartered in Tysons Corner, Virginia in the United States. These six cities provide 8,900 km of training data and over. was a provider of VSAT satellite-based data network services as well as hybrid satellite/terrestrial networks and network management services. For training purposes we utilize both the SpaceNet 3 and SpaceNet 5 data, as described here. ![]() Note that the total contribution to the total NN’s ensembled is listed in parentheses in the Architectures column. Acquired by SageNet in 2014, Spacenet, Inc. The model architectures, ensemble and pre-training schemes, as well as training and inference time for each of the winning solutions. The first two of these competitions focused on automated building footprint extraction, and the most recent challenge focused on road network extraction. We also report model precision (ratio of false predictions) and recall (ratio of missed ground truth polygons): The SpaceNet partners also launched a series of public prize competitions to encourage improvement of remote sensing machine learning algorithms. The overall score represents the SpaceNet Metric (x 100) for the entire scoring set. It contains 67,000 square km of very high-resolution imagery, >11M building footprints, and 20,000 km of road labels to ensure that there is adequate open source data available for geospatial machine learning research. See the blog post on CosmiQ Works' blog The DownlinQ for an additional summary.Ĭompetitors’ scores in the SpaceNet 6: Multi-Sensor All Weather Mapping Challenge compared to the baseline model. The SpaceNet Dataset is hosted as an Amazon Web Services (AWS) Public Dataset. Each subdirectory contains the competitors' written descriptions of their solution to the challenge. The five subdirectories in this repository comprise the code for the winning solutions of SpaceNet 7 hosted by TopCoder. Each subdirectory contains the competitors' written descriptions of their solution to the challenge. The SpaceNet 7 Multi-temporal Urban Development Challenge Winning Solutions Summary. The five subdirectories in this repository comprise the code for the winning solutions of SpaceNet 6: Multi-Sensor All Weather Mapping Challenge hosted by TopCoder. Versatile, resourceful and forward thinking project and change management professional with over 20 years experience. SpaceNet 6: Multi-Sensor All Weather Mapping Competitor Solutions
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