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GTC On-Demand

AI and DL Research
Presentation
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Simultaneous Pixel-Localization and Feature Extraction for Multiple Instances in a Scene
We'll introduce attendees to a new deep learning approach to object-localization. Instead of bounding boxes, our network estimates the center pixel locations for a variable number of targets in a scene while simultaneously extracting a characteristic feature-set. We'll outline the overall approach and describe the underlying network architecture and training. We'll also present the results of our network as applied to the cars overhead with context dataset and discuss the current and future possibilities of this approach.
We'll introduce attendees to a new deep learning approach to object-localization. Instead of bounding boxes, our network estimates the center pixel locations for a variable number of targets in a scene while simultaneously extracting a characteristic feature-set. We'll outline the overall approach and describe the underlying network architecture and training. We'll also present the results of our network as applied to the cars overhead with context dataset and discuss the current and future possibilities of this approach.  Back
 
Keywords:
AI and DL Research, Computer Vision, GTC Silicon Valley 2018 - ID S8191
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