Let’s say you need to generate a large-scale information product. Maybe an impervious surface map or land use/land cover map. You’ll need high-powered analytics, access to data, and the computing power to chew through it all. But it’s a short term project that will wrap up in a month, maybe two.
CloudEO and Harris have partnered to offer ENVI in the Cloud; a cloud-deployed version of desktop ENVI. Just log-in and start working – it’s that easy!
Wondering how you can use machine learning, and more specifically deep learning technologies, to get a jump on the competition? This webinar will provide a brief, high-level overview of machine learning and its applications before delving into Harris’ five year head start developing deep learning technologies that are being deployed today. Harris has applied…
Let’s say you need to generate a large-scale information product. Maybe an impervious surface map or...
Wondering how you can use machine learning, and more specifically deep learning technologies, to get a...
Author: Abby Lehman/Wednesday, May 28, 2014/Categories: Webinars, IDL Webinar, ENVI Webinar
Significant improvements in speeds for imagery orthorectification, atmospheric correction, and image transformations like Independent Components Analysis (ICA) have been achieved using GPU-based implementations. Additional optimizations, when factored in with GPU processing capabilities, can provide 50x -- 100x reduction in the time required to process large imagery.
Exelis Visual Information Solutions (VIS) has implemented a CUDA-based GPU processing frame work for accelerating ENVI and IDL processes that can best take advantage of parallelization.
Join Amanda O'Connor as she discusses her presentation, "Using GPU's to Accelerate Orthorectification, Atmospheric Correction, and Transformations for Big Data," originally presented at the 2013 AGU Conference.
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