EmoNet speech-emotion CNN reports 96.75% accuracy with 4.11M parameters
The model classifies seven emotions on combined TESS, RAVDESS and SAVEE data using a separable CNN and BiLSTM.
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Stories tagged #bilstm
Cybersecurity in Edge Computing: A Trust-Aware Federated Hybrid Intrusion Detection Framework
Researchers propose a trust-aware federated hybrid IDS that detects edge attacks without sharing raw telemetry.
A Gmail-Based Phishing Detection Prototype for Nigerian Fintech Emails Using Sender Checks and BiLSTM Classification
A Gmail extension prototype detects Nigerian fintech phishing with sender checks and a BiLSTM classifier.