A transfer learning model using thermal images reaches 98.8% accuracy for recognizing breathing patterns.
Deep transfer learning for automatic speech recognition: Towards better generalization
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
A SE-enhanced ViT-BiLSTM hybrid model reports 99.33% accuracy on EdgeIIoT and 98.16% on CICIoMT2024 for intrusion detection after data balancing.
A ResNet-1D-BiGRU model with multi-head attention reaches 98.71% accuracy on EdgeHoTset and 99.99% on CICIoV2024 for IIoT intrusion detection while keeping inference under 0.0002 seconds per sample.
citing papers explorer
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BreathAI: Transfer Learning-Based Thermal Imaging for Automated Breathing Pattern Recognition
A transfer learning model using thermal images reaches 98.8% accuracy for recognizing breathing patterns.
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SE-Enhanced ViT and BiLSTM-Based Intrusion Detection for Secure IIoT and IoMT Environments
A SE-enhanced ViT-BiLSTM hybrid model reports 99.33% accuracy on EdgeIIoT and 98.16% on CICIoMT2024 for intrusion detection after data balancing.
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Hybrid ResNet-1D-BiGRU with Multi-Head Attention for Cyberattack Detection in Industrial IoT Environments
A ResNet-1D-BiGRU model with multi-head attention reaches 98.71% accuracy on EdgeHoTset and 99.99% on CICIoV2024 for IIoT intrusion detection while keeping inference under 0.0002 seconds per sample.