NVIDIA Computer Vision
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NVIDIA Computer Vision
What’s New in Computer Vision
On-Demand Session: Accelerating Kubernetes with NVIDIA Operators
NVIDIA Operators streamline installing and managing GPUs and NICs on Kubernetes to make the software stack ready to run the most resource-demanding workloads, such as AI, ML, DL, and HPC, in the cloud, data center, and at the edge.
Achieving FP32 Accuracy for INT8 Inference Using Quantization Aware Training with NVIDIA TensorRT
○ TensorRT is an SDK for high-performance deep learning inference and with TensorRT 8.0, you can import models trained using Quantization Aware Training (QAT) to run inference in INT8 precision without losing FP32 accuracy. QAT significantly reduces compute required and storage overhead for efficient inference.
Computer Vision: Real-World Applications
No challenge is too small and no company too big for computer vision. See innovative solutions in action—from startups to global manufacturers.
Improving Mobility for People with Low Vision (Biel Glasses) impaired
Increasing Vehicle Quality Using Computer Vision and AI (Audi)
Deploying NGC Models with Maximo Visual Inspection (IBM)
Dive In with the Deep Learning Institute
Learn the Fundamentals of Computer Vision
New to computer vision? Want a primer before jumping in? Learn the Fundamentals of Deep Learning with hands-on exercises for CV in this eight-hour course offered by the Deep Learning Institute. You’ll learn how to train deep learning models from scratch and use pre-trained models, experiment with different model architectures, explore deep learning tools and techniques, and work with datasets to improve model accuracy. You’ll also earn a certification to show your accomplishment.
Partnering for Success
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