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1
Intro
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CHALLENGES WITH VIDEO ANALYTICS
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CREATE AI - TRANSFER LEARNING
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NVIDIA TRANSFER LEARNING TOOLKIT (TLT)
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TLT WORKFLOW
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ACHIEVING ACCURACY WITH SMALL DATASET
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MODEL PRUNING
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TLT NETWORK ROADMAP
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PURPOSE BUILT PRE-TRAINED NETWORKS
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MODEL PERFORMANCE
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IVA APPLICATION WORKFLOW
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DEEPSTREAM SOFTWARE STACK
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DEEPSTREAM - MANY INDUSTRIES, FLEXIBLE DEPLOYMENT
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DEEPSTREAM GRAPH ARCHITECTURE
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DEEPSTREAM ROADMAP
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END-TO-END DEEP LEARNING WORKFLOW
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PYTHON SUPPORT
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DEEPSTREAM WITH TRITON INFERENCE SERVER
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AT-SCALE DEPLOYMENT
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BI-DIRECTIONAL IOT COMMUNICATION
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OTA MODEL UPDATE
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SMART RECORD
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SECURITY
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SUMMARY
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GET STARTED TODAY
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DEVELOPER RESOURCES
Description:
Explore NVIDIA's tools for training, building, and deploying intelligent vision applications at the edge in this comprehensive one-hour video. Discover how to process data from sensors, cameras, and IoT devices, train with large datasets, and deploy real-time, high-throughput, low-latency video analytics pipelines. Learn to optimize training workflows and leverage pre-trained models for applications like smart parking, infrastructure monitoring, disaster relief, retail analytics, and logistics. Gain insights into NVIDIA's suite of tools for creating, building, and deploying video apps that deliver business efficiency. Explore topics such as transfer learning, the NVIDIA Transfer Learning Toolkit (TLT), achieving accuracy with small datasets, model pruning, purpose-built pre-trained networks, DeepStream software stack, and end-to-end deep learning workflows. Understand the challenges of video analytics, IVA application workflows, and at-scale deployment strategies, including bi-directional IoT communication and OTA model updates. Access developer resources and join the NVIDIA Developer Community to further enhance your skills in building intelligent vision applications. Read more

NVIDIA Tools for Training and Deploying Intelligent Vision Applications at the Edge

Nvidia
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