IEEE

Anomaly Detection for Identity Authentication Using 1D-CNN-LSTM Autoencoder and Doppler Radar with Classifiers

Abstract: This study presents an integrated framework combining 1D-CNN-LSTM-Autoencoder-based anomaly detection with identity authentication using machine learning classifiers. The 1D-CNN-LSTM ...
IEEE

AE-CNN Ensemble: A Novel Architecture for Effective Network Intrusion Detection and Classification

Abstract: The escalating scale and sophistication of cyberattacks pose a formidable challenge to conventional intrusion detection systems (IDS) because they lack the flexibility to adapt to evolving ...
IEEE

Accurate Simulation Pipeline for Passive Single-Photon Imaging

Abstract: Single-Photon Avalanche Diodes (SPADs) are new and promising imaging sensors. These sensors are sensitive enough to detect individual photons hitting each pixel, with extreme temporal ...
IEEE

Performance Enhancement of Human Activity Recognition Using Millimeter-Wave Multi-Link Channels

Abstract: Human activity recognition (HAR) using millimeter-wave (mmWave) radar has gained attention as a contactless and privacy-preserving sensing method that remains effective under low lighting ...
IEEE

Advancing Deep-fake Detection: A Hybrid CNN-Gradient Boosting Classifier Approach

Abstract: Discerning the veritable from the counterfeit in our digital milieu has become an exceedingly formidable enterprise, particularly in light of the meteoric rise of deepfake technology. In ...
IEEE

An Integrated Time-Frequency Detector and Radar Pulse Modulation CNN Classifier

Abstract: Radar pulse detection and intra-pulse modulation classification are important capabilities in electronic warfare (EW) applications, including electronic intelligence (ELINT), electronic ...
IEEE

Muscle-Joint Feature Fusion for Swimming Pattern Recognition With 1D-CNN Classifier

Abstract: Swimming pattern recognition plays an important role in underwater wearable robot control and competitive sports training. However, serious disturbances of harsh underwater environments ...
IEEE

Parallel two-class 3D-CNN classifiers for video classification

Abstract: The required amount of computation and training data for training 3D-CNN, especially for complex classification tasks with videos, hinders the wide application of 3D-CNN. In this paper, ...