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Evaluating and Enhancing Face Anti-Spoofing Algorithms for Light Makeup: A General Detection Approach.
Sensors (Basel)
December 2024
School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.
Makeup modifies facial textures and colors, impacting the precision of face anti-spoofing systems. Many individuals opt for light makeup in their daily lives, which generally does not hinder face identity recognition. However, current research in face anti-spoofing often neglects the influence of light makeup on facial feature recognition, notably the absence of publicly accessible datasets featuring light makeup faces.
View Article and Find Full Text PDFCloud-Edge-End Collaborative Federated Learning: Enhancing Model Accuracy and Privacy in Non-IID Environments.
Sensors (Basel)
December 2024
School of Computer Science and Engineering, Southwest Minzu University, Chengdu 610041, China.
Cloud-edge-end computing architecture is crucial for large-scale edge data processing and analysis. However, the diversity of terminal nodes and task complexity in this architecture often result in non-independent and identically distributed (non-IID) data, making it challenging to balance data heterogeneity and privacy protection. To address this, we propose a privacy-preserving federated learning method based on cloud-edge-end collaboration.
View Article and Find Full Text PDFEvaluation and Anomaly Detection Methods for Broadcast Ephemeris Time Series in the BeiDou Navigation Satellite System.
Sensors (Basel)
December 2024
School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Liuxia Street, Hangzhou 310023, China.
Broadcast ephemeris data are essential for the precision and reliability of the BeiDou Navigation Satellite System (BDS) but are highly susceptible to anomalies caused by various interference factors, such as ionospheric and tropospheric effects, solar radiation pressure, and satellite clock biases. Traditional threshold-based methods and manual review processes are often insufficient for detecting these complex anomalies, especially considering the distinct characteristics of different satellite types. To address these limitations, this study proposes an automated anomaly detection method using the IF-TEA-LSTM model.
View Article and Find Full Text PDFAge of Information Analysis for Multi-Priority Queue and Non-Orthoganal Multiple Access (NOMA)-Enabled Cellular Vehicle-to-Everything in Internet of Vehicles.
Sensors (Basel)
December 2024
Qualcomm, San Jose, CA 95110, USA.
With the development of Internet of Vehicles (IoV) technology, the need for real-time data processing and communication in vehicles is increasing. Traditional request-based methods face challenges in terms of latency and bandwidth limitations. Mode 4 in cellular vehicle-to-everything (C-V2X), also known as autonomous resource selection, aims to address latency and overhead issues by dynamically selecting communication resources based on real-time conditions.
View Article and Find Full Text PDFMeasurement Properties of Wearable Kinematic-Based Data Collection Systems to Evaluate Ball Kicking in Soccer: A Systematic Review with Evidence Gap Map.
Sensors (Basel)
December 2024
Applied Neuromechanics Research Group, Laboratory of Neuromechanics, Federal University of Pampa (Unipampa), P.O. Box 118, Uruguaiana 97500-970, RS, Brazil.
Kinematic assessment of ball kicking may require significant human effort (e.g., traditional vision-based tracking systems).
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