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Abstract:
SOFWERX developed a vision-based classifier using commodity hardware and machine learning libraries to satisfy an urgent high-level requirement. To track the usage of tank ammunition, the team had to address challenges involving unavailable training data, varying spatial orientations, and limited power consumption. To resolve these challenges, SOFWERX generated an augmented dataset using synthetic models, implemented spatial transformers, and experimented with different hardware/software optimizations.
SOFWERX developed a vision-based classifier using commodity hardware and machine learning libraries to satisfy an urgent high-level requirement. To track the usage of tank ammunition, the team had to address challenges involving unavailable training data, varying spatial orientations, and limited power consumption. To resolve these challenges, SOFWERX generated an augmented dataset using synthetic models, implemented spatial transformers, and experimented with different hardware/software optimizations.  Back
 
Topics:
AI Application Deployment and Inference, Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8193
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