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1 to 7 of 7 Results
Benchmarking Deep Learning Inference of Remote Sensing Imagery on the Qualcomm Snapdragon and Intel Movidius Myriad X Processors Onboard the International Space Station
Jul 17, 2022
Jason Swope, 2022, "Benchmarking Deep Learning Inference of Remote Sensing Imagery on the Qualcomm Snapdragon and Intel Movidius Myriad X Processors Onboard the International Space Station", https://doi.org/10.48577/jpl.WPXENU, IEEE IGARSS 2022 (Virtual/In-Person Hybrid), JPL Open Repository
As space missions become more distant, the need for onboard analysis and image recognition becomes even more important. Deep learning is state of the art in computer vision [1], so our goal is to demonstrate onboard inference with these algorithms. Traditional flight hardware pro...
Benchmarking Remote Sensing Image Processing and Analysis on the Snapdragon Processor Onboard the International Space Station
Jul 17, 2022
Jason Swope, 2022, "Benchmarking Remote Sensing Image Processing and Analysis on the Snapdragon Processor Onboard the International Space Station", https://doi.org/10.48577/jpl.USZGLU, IEEE IGARSS 2022 (Virtual/In-Person Hybrid), JPL Open Repository
Future space missions will process and analyze imagery onboard placing greater demands on flight computing. Traditional flight hardware provides modest compute especially compared to laptop and desktop computers. A new generation of commercial off the shelf (COTS) processors, suc...
BENCHMARKING REMOTE SENSING IMAGE PROCESSING AND ANALYSIS ON THE SNAPDRAGON PROCESSOR ONBOARD THE INTERNATIONAL SPACE STATION
Jul 17, 2022
Jason Swope, 2022, "BENCHMARKING REMOTE SENSING IMAGE PROCESSING AND ANALYSIS ON THE SNAPDRAGON PROCESSOR ONBOARD THE INTERNATIONAL SPACE STATION", https://doi.org/10.48577/jpl.QWWZMH, IEEE IGARSS 2022 (Virtual/In-Person Hybrid), JPL Open Repository
No abstract available.
Benchmarking Deep Learning Inference of Remote Sensing Imagery on the Qualcomm Snapdragon and Intel Movidius Myriad X Processors Onboard the International Space Station
Jul 17, 2022
Jason Swope, 2022, "Benchmarking Deep Learning Inference of Remote Sensing Imagery on the Qualcomm Snapdragon and Intel Movidius Myriad X Processors Onboard the International Space Station", https://doi.org/10.48577/jpl.MPC5FG, IEEE IGARSS 2022 (Virtual/In-Person Hybrid), JPL Open Repository
No abstract available.
TESTING MARS ROVER, SPECTRAL UNMIXING, AND SHIP DETECTION NEURAL NETWORKS, AND MEMORY CHECKERS ON EMBEDDED SYSTEMS ONBOARD THE ISS
May 31, 2022
Jason Swope, 2022, "TESTING MARS ROVER, SPECTRAL UNMIXING, AND SHIP DETECTION NEURAL NETWORKS, AND MEMORY CHECKERS ON EMBEDDED SYSTEMS ONBOARD THE ISS", https://doi.org/10.48577/jpl.QW2N1B, 16th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA 2022), JPL Open Repository
Future space missions can benefit from processing imagery onboard to detect science events, create insights, and respond autonomously. This capability can enable the discovery of new science. One of the challenges to this mission concept is that traditional space flight hardware...
BENCHMARKING REMOTE SENSING IMAGE PROCESSING AND MISSION PLANNING APPLICATIONS ON THE SNAPDRAGON PROCESSOR ONBOARD THE INTERNATIONAL SPACE STATION
May 31, 2022
Jason Swope, 2022, "BENCHMARKING REMOTE SENSING IMAGE PROCESSING AND MISSION PLANNING APPLICATIONS ON THE SNAPDRAGON PROCESSOR ONBOARD THE INTERNATIONAL SPACE STATION", https://doi.org/10.48577/jpl.X76JVE, 16th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA 2022), JPL Open Repository
Future space missions will process and analyze imagery onboard and plan and act more autonomously placing greater demands on flight computing. Traditional flight hardware provides modest compute, even when compared to laptop and desktop computers. A new generation of commercial o...
Validation of Flight Software on the Qualcomm Snapdragon 855 on the International Space Station
Feb 7, 2022
Jason Swope, 2022, "Validation of Flight Software on the Qualcomm Snapdragon 855 on the International Space Station", https://doi.org/10.48577/jpl.XWNU6Q, VIRTUAL 2022 Flight Software Workshop, JPL Open Repository
No abstract available.
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