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2020 – today
- 2024
[c8]Elyes Manai, Mohamed Mejri, Jaouhar Fattahi:
Confusion Matrix Explainability to Improve Model Performance: Application to Network Intrusion Detection. CoDIT 2024: 1-5- [c7]Elyes Manai, Mohamed Mejri, Jaouhar Fattahi:
Intrusion Detection Explainability by Ensemble Learning with a Case Study. CoDIT 2024: 1542-1547 - [c6]Jaouhar Fattahi, Baha Eddine Lakdher, Mohamed Mejri, Ridha Ghayoula, Elyes Manai, Marwa Ziadia:
FingFor: a Deep Learning Tool for Biometric Forensics. CoDIT 2024: 1667-1672 - [c5]Elyes Manai, Mohamed Mejri, Jaouhar Fattahi:
Minimizing Model Misclassification Using Regularized Loss Interpretability. IIAI-AAI 2024: 231-236 - [c4]Jaouhar Fattahi, Feriel Sghaier, Mohamed Mejri, Sahbi Bahroun, Ridha Ghayoula, Elyes Manai:
Cyberbullying Detection Using Bag-of-Words, TF-IDF, Parallel CNNs and BiLSTM Neural Networks. SoMeT 2024: 72-84 - [c3]Jaouhar Fattahi, Feriel Sghaier, Mohamed Mejri, Elyes Manai, Ridha Ghayoula:
Recognition of Handwritten Tamazight Characters Using ResNet, MobileNet and VGG Transfer Learning. SoMeT 2024: 429-440 - [c2]Elyes Manai
, Mohamed Mejri, Jaouhar Fattahi:
Fingerprint Fraud Explainability Using Grad-Cam for Forensic Procedures. SoMeT 2024: 457-470 - 2023
- [c1]Elyes Manai, Mohamed Mejri, Jaouhar Fattahi:
Impact of Feature Encoding on Malware Classification Explainability. ECAI 2023: 1-6 - [i1]Elyes Manai, Mohamed Mejri, Jaouhar Fattahi:
Impact of Feature Encoding on Malware Classification Explainability. CoRR abs/2307.05614 (2023)
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