AINeutralarXiv – CS AI · Mar 34/103
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A Neural Network-Based Real-time Casing Collar Recognition System for Downhole Instruments
Researchers developed Collar Recognition Nets (CRNs), lightweight neural networks for real-time recognition of casing collar signatures in downhole oil/gas operations. The system achieves 97.2% accuracy with only 1,985 parameters and processes 1,000 inferences per second on embedded ARM hardware.