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GTC On-Demand

AI Application Deployment and Inference
Presentation
Media
Prototyping Vision-Based Classifiers in Constrained Environments
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
 
Keywords:
AI Application Deployment and Inference, Performance Optimization, GTC Silicon Valley 2018 - ID S8193
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Medical Imaging and Radiology
Presentation
Media
Recognizing Cancerous Cells in Histology Imagery Using Deep Learning
We'll present the results of applying deep learning techniques and GPUs towards classification of histology imagery. At Naval Medical Center, San Diego, pathologists manually inspect biopsy samples to identify cancerous cells amid healthy tissue. This process is time-intensive and susceptible to errors caused by fatigue. Using DIGITS, Caffe and GPUs, researchers are automating this process.
We'll present the results of applying deep learning techniques and GPUs towards classification of histology imagery. At Naval Medical Center, San Diego, pathologists manually inspect biopsy samples to identify cancerous cells amid healthy tissue. This process is time-intensive and susceptible to errors caused by fatigue. Using DIGITS, Caffe and GPUs, researchers are automating this process.  Back
 
Keywords:
Medical Imaging and Radiology, Deep Learning and AI, Press-Suggested Sessions: AI & Deep Learning, GTC Silicon Valley 2016 - ID S6442
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