Improving IoT security with explainable AI: quantitative evaluation of explainability for IoT botnet detection
An Efficient Neural Network for the Diagnosis of Parkinson’s Disease Using Dynamic Handwriting Analysis
Wave density spectra estimation with LSTM from Sentinel-1 SAR in the Baltic Sea
Enhancing IoT Botnet attack detection in SOCs with an explainable active learning framework
Explainable transformer-based intrusion detection in Internet of Medical Things (IoMT) networks
Explainable federated learning for botnet detection in IoT networks
Machine learning-based analysis of human motions for Parkinson’s disease diagnostics
Transforming fatigue assessment: Smartphone-based system with digitized motor skill tests
Deep learning based segmentation of Luria’s alternating series test to support diagnostics of Parkinson’s disease
Application of the LSTM models for Baltic Sea wave spectra estimation
A light-weight CNN model for efficient Parkinson’s disease diagnostics
Improving transparency and explainability of deep learning based IoT botnet detection using explainable artificial intelligence (XAI)