Orbital Insight is a Geospatial Big Data company leveraging the rapidly growing availability of satellite, UAV, and other geospatial data sources. Our goal is to understand and characterize useful trends at global, regional, and hyperlocal scales. Backed by top tier VCs, including Sequoia, Google Ventures, and Bloomberg Beta, we build products that have never existed before, and could not exist without the ongoing proliferation of rich geospatial data sources, computer vision & deep learning, and inexpensive cloud computing.
Orbital Insight is a Geospatial Big Data company leveraging the rapidly growing availability of satellite, UAV, and other geospatial data sources. Our goal is to understand and characterize useful trends at global, regional, and hyperlocal scales. Backed by top tier VCs, including Sequoia, Google Ventures, and Bloomberg Beta, we build products that have never existed before, and could not exist without the ongoing proliferation of rich geospatial data sources, computer vision & deep learning, and inexpensive cloud computing.
Orbital Insight is a Geospatial Big Data company leveraging the rapidly growing availability of satellite, UAV, and other geospatial data sources. Our goal is to understand and characterize useful trends at global, regional, and hyperlocal scales. Backed by top tier VCs, including Sequoia, Google Ventures, and Bloomberg Beta, we build products that have never existed before, and could not exist without the ongoing proliferation of rich geospatial data sources, computer vision & deep learning, and inexpensive cloud computing.
Orbital Insight is a Geospatial Big Data company leveraging the rapidly growing availability of satellite, UAV, and other geospatial data sources. Our goal is to understand and characterize useful trends at global, regional, and hyperlocal scales. Backed by top tier VCs, including Sequoia, Google Ventures, and Bloomberg Beta, we build products that have never existed before, and could not exist without the ongoing proliferation of rich geospatial data sources, computer vision & deep learning, and inexpensive cloud computing.
Orbital Insight is a Geospatial Big Data company leveraging the rapidly growing availability of satellite, UAV, and other geospatial data sources. Our goal is to understand and characterize useful trends at global, regional, and hyperlocal scales. Backed by top tier VCs, including Sequoia, Google Ventures, and Bloomberg Beta, we build products that have never existed before, and could not exist without the ongoing proliferation of rich geospatial data sources, computer vision & deep learning, and inexpensive cloud computing.
Orbital Insight is a Geospatial Big Data company leveraging the rapidly growing availability of satellite, UAV, and other geospatial data sources. Our goal is to understand and characterize useful trends at global, regional, and hyperlocal scales. Backed by top tier VCs, including Sequoia, Google Ventures, and Bloomberg Beta, we build products that have never existed before, and could not exist without the ongoing proliferation of rich geospatial data sources, computer vision & deep learning, and inexpensive cloud computing.
Orbital Insight is a Geospatial Big Data company leveraging the rapidly growing availability of satellite, UAV, and other geospatial data sources. Our goal is to understand and characterize useful trends at global, regional, and hyperlocal scales. Backed by top tier VCs, including Sequoia, Google Ventures, and Bloomberg Beta, we build products that have never existed before, and could not exist without the ongoing proliferation of rich geospatial data sources, computer vision & deep learning, and inexpensive cloud computing.
Tacking on a shameless recruiting plug: if you're interesting in computer vision, deep learning, and/or satellite imagery, Orbital Insight is hiring! http://orbitalinsight.com/jobs/machine_vision.html
Responding to the parent comment, in terms of running time, the primary bottleneck is the RCNN localization portion; that takes about a minute and a half on my laptop to process a single image. In the Future Work section of the blog post I talk about collapsing the entire detection and localization pipeline into a single deconvolution network that directly takes in raw images and outputs image masks. The hope is that this runs much faster at inference time.
