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Dr. A. Vance Principal Researcher

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home / Intelligence / Telecom AI Graph

Network Optimization - 5G Slicing LIVE

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Telecom AI

Dr. Sarah C. Expert

Prof. A. Ray Synthetic

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Deep ResNets for 5G

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SYNTH-DATA-042

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Successfully fetched 154 nodes and 342 edges.

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article Paper Verified Source

Deep Residual Learning for Image Recognition in 5G Networks

calendar_today 2016

format_quote 182k Citations

trending_up High Impact

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Radio Access Network (RAN) 98% Match

Core Network AI 45% Match

Knowledge Graph Tags

Deep Learning Computer Vision Neural Networks Optimization

Abstract

Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. This architecture is pivotal for modern telecom AI applications where low-latency inference is critical.

Key Contributors

Kaiming He Facebook AI Research

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