Muhammad Khuram Shahzad
PulseAugur coverage of Muhammad Khuram Shahzad — every cluster mentioning Muhammad Khuram Shahzad across labs, papers, and developer communities, ranked by signal.
-
New SHIELD-IDS enhances ML intrusion detection against adversarial attacks
Researchers have developed SHIELD-IDS, an enhanced intrusion detection system designed to combat adversarial attacks on machine learning models. The system integrates gradient boosting models like XGBoost and LightGBM i…
-
New MIRAGE method enhances MSR dataset analysis with metadata and FAIRness
Researchers have developed MIRAGE, a new method for analyzing Mining Software Repositories (MSR) datasets by enhancing their metadata and assessing FAIRness. This approach uses the Semantic Scholar API to gather data fr…
-
CNN-LSTM model boosts IoT intrusion detection accuracy to 97%
Researchers have developed an improved intrusion detection system for IoT networks utilizing a CNN-LSTM model. This system integrates multi-class classification and temporal feature learning to enhance detection accurac…
-
New method boosts license plate recognition accuracy and speed
Researchers have developed a new method to improve real-time license plate detection and recognition (LPDR) systems. The approach addresses issues of spatial character mismatches and data imbalance in training sets by i…
-
New blockchain federated learning framework boosts efficiency
Researchers have introduced TITAN-FedAnil+, a novel framework for blockchain-enabled federated learning designed for resource-constrained intelligent enterprises. This system addresses challenges like data heterogeneity…
-
Enhanced WT-PSE framework improves medical image segmentation
Researchers have enhanced a medical image segmentation framework called WT-PSE, originally designed for robust cross-domain segmentation. The improvements focus on addressing limitations in the initial implementation, i…
-
HYolo integrates hypergraph learning to boost IoT object detection
Researchers have developed HYolo, a new object detection framework for IoT devices that integrates hypergraph learning with the YOLO architecture. This approach aims to capture complex, high-order relationships between …
-
AI enhances IoT intrusion detection with improved accuracy and efficiency
Researchers have enhanced an existing autonomous online intrusion detection system (AOC-IDS) for Internet of Things (IoT) devices by addressing limitations in class imbalance, pseudo-label generation, generalization, an…