Case Study

Scaling Up AI-Enabled Video Analytics Applications on NVIDIA Jetson Devices

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AI-enabled video analytics applications are being deployed today across many different industries such as smart city, security cameras, healthcare, smart retail, and sports tech, among others.

While these applications are designed to support a wide variety of use cases, there are many shared challenges faced by AI developers across industries. Developers need to ensure that the computer vision models that power video analytics applications are accurate, can deliver real-time insights, and run in a cost-efficient manner.

In this case study, learn how three of Deci’s customers have scaled up AI-enabled video analytics solutions across various verticals using our Neural Architecture Search (NAS) based deep learning development platform.

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					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")

model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")