Husnain Mushtaq

Orcid: 0009-0002-3532-5510

According to our database1, Husnain Mushtaq authored at least 12 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Securing internet of vehicles: a blockchain-based federated learning approach for enhanced intrusion detection.
Clust. Comput., August, 2025

Trans-LGS: Transformer-Based Local Graph Structure for 3D Object Detection in Autonomous Vehicles.
IEEE Trans. Veh. Technol., April, 2025

GFA-SMT: Geometric Feature Aggregation and Self-Attention in a Multi-Head Transformer for 3D Object Detection in Autonomous Vehicles.
IEEE Trans. Intell. Transp. Syst., March, 2025

IoV-SFL: A blockchain-based federated learning framework for secure and efficient data sharing in the internet of vehicles.
Peer Peer Netw. Appl., February, 2025

Point Class-Adaptive Transformer (PCaT): A Novel Approach for Efficient Point Cloud Classification and Segmentation.
Expert Syst. J. Knowl. Eng., February, 2025

SC3D: Semantic-guided and Class-adaptive cross-domain fusion for 3D object detection in autonomous vehicles.
Expert Syst. Appl., 2025

CLS-3D: Content-Wise LiDAR-Camera Fusion and Slot Reweighting Transformer for 3D Object Detection in Autonomous Vehicles.
IEEE Access, 2025

2024
O2SAT: Object-Oriented-Segmentation-Guided Spatial-Attention Network for 3D Object Detection in Autonomous Vehicles.
Inf., July, 2024

Channelwise and Spatially Guided Multimodal Feature Fusion Network for 3-D Object Detection in Autonomous Vehicles.
IEEE Trans. Geosci. Remote. Sens., 2024

SecBFL-IoV: A Secure Blockchain-Enabled Federated Learning Framework for Resilience Against Poisoning Attacks in Internet of Vehicles.
Proceedings of the Pattern Recognition and Computer Vision - 7th Chinese Conference, 2024

2023
A verifiable and privacy-preserving blockchain-based federated learning approach.
Peer Peer Netw. Appl., September, 2023

2021
Mining software architecture knowledge: Classifying stack overflow posts using machine learning.
Concurr. Comput. Pract. Exp., 2021


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