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Author: 21649

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Wisdom of Crowds: A Human-Machine-Things Cooperative Scheduling Method for Heterogeneous Mobile Crowdsensing

Relying on the development of crowdsourcing ideas and mobile crowd sensing (MCS) technology, many tasks that originally required a lot of manpower and material resources have been solved efficiently. However, with the development of urbanization, the traditional MCS systems have gradually been unable to cope with the…

Yimeng Liu et al.Yonsei University

Session 2c: Blind Users and Collaborative Sensing

LiqDetector: Enabling Container-Independent Liquid Detection with mmWave Signals Based on a Dual-Reflection Model

Wang等人提出LiqDetector毫米波液体检测系统，采用双反射模型突破容器限制，实现高灵敏度液体类型识别。

Zhu Wang et al.

EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control

Li 等人提出 EchoPFL 框架，通过异步本地训练和按需陈旧度控制实现移动端高效的个性化联邦学习，保护用户隐私。

Xiaochen Li et al.Northwestern Polytechnical University

GrainSense: A Wireless Grain Moisture Sensing System based on Wi-Fi Signals

Wang 等人开发 GrainSense 系统，利用 Wi-Fi 信号无接触测量谷物水分，实现仓储谷物湿度的实时无线监测。

Zhu Wang et al.Northwestern Polytechnical University

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Understanding the Mechanism of Through-Wall Wireless Sensing: A Model-based Perspective

"During the last few years, there is a growing interest on the usage of Wi-Fi signals for human activity detection. A large number of Wi-Fi based sensing systems have been developed, including respiration detection, gesture classification, identity recognition, etc. However, the usability and robustness of such system…

Hualei Zhang et al.Northwestern Polytechnical University

sUrban: Stable Prediction for Unseen Urban Data from Location-based Sensors

"Recent machine learning research on smart cities has achieved great success in predicting future trends, under the key assumption that the test data follows the same distribution of the training data. The rapid urbanization, however, makes this assumption challenging to hold in practice. Because new data is emerging…

Qianru Wang et al.Northwestern Polytechnical University

AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices

"The ubiquity of camera-embedded devices and the advances in deep learning have stimulated various intelligent mobile video applications. These applications often demand on-device processing of video streams to deliver real-time, high-quality services for privacy and robustness concerns. However, the performance of th…

Sicong Liu et al.Northwestern Polytechnical University

Genie in the Model: Automatic Generation of Human-in-the-Loop Deep Neural Networks for Mobile Applications

"Advances in deep neural networks (DNNs) have fostered a wide spectrum of intelligent mobile applications ranging from voice assistants on smartphones to augmented reality with smart-glasses. To deliver high-quality services, these DNNs should operate on resource-constrained mobile platforms and yield consistent perfo…

Yanfei Wang et al.Northwestern Polytechnical University

VPRNet: Voxel-based Efficient and Partial-to-Partial Point Cloud Registration on Mobile Devices

With the popularity of embedded devices such as LIDAR sensors and depth cameras, the resulting point clouds become the main data format for representing the 3D world and spawn various smart mobile applications. A key technology for enabling these applications to furnish high-quality services is real-time point cloud r…

Zihao Yin et al.Northwestern Polytechnical University

Task Execution Quality Maximization for Mobile Crowdsourcing in Geo-Social Networks

With the rapid development of smart devices and high-quality wireless technologies, mobile crowdsourcing (MCS) has been drawing increasing attention with its great potential in collaboratively completing complicated tasks on a large scale. A key issue toward successful MCS is participant recruitment, where a MCS platf…

Liang Wang et al.Northwestern Polytechnical University

Crowds and Collaboration

Human-Machine Cooperative Video Anomaly Detection

It is still a challenge to detect anomalous events in video sequences in the field of computer vision due to heavy object occlusions, varying crowded densities and complex situations. To address this, we propose a novel human-machine cooperative approach which uses human feedback on anomaly confirmation to inform and…

Fan Yang et al.Northwestern Polytechnical University

Human-AI Collaboration / Images in AI

Paper Title	Authors	Research Topics
Wisdom of Crowds: A Human-Machine-Things Cooperative Scheduling Method for Heterogeneous Mobile Crowdsensing Relying on the development of crowdsourcing ideas and mobile crowd sensing (MCS) technology, many tasks that originally required a lot of manpower and material resources have been solved efficiently. However, with the development of urbanization, the traditional MCS systems have gradually been unable to cope with the…	YL Yimeng Liu et al.Yonsei University	Session 2c: Blind Users and Collaborative Sensing
LiqDetector: Enabling Container-Independent Liquid Detection with mmWave Signals Based on a Dual-Reflection Model Wang等人提出LiqDetector毫米波液体检测系统，采用双反射模型突破容器限制，实现高灵敏度液体类型识别。	ZW Zhu Wang et al.
EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control Li 等人提出 EchoPFL 框架，通过异步本地训练和按需陈旧度控制实现移动端高效的个性化联邦学习，保护用户隐私。	XL Xiaochen Li et al.Northwestern Polytechnical University
GrainSense: A Wireless Grain Moisture Sensing System based on Wi-Fi Signals Wang 等人开发 GrainSense 系统，利用 Wi-Fi 信号无接触测量谷物水分，实现仓储谷物湿度的实时无线监测。	ZW Zhu Wang et al.Northwestern Polytechnical University
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
Understanding the Mechanism of Through-Wall Wireless Sensing: A Model-based Perspective "During the last few years, there is a growing interest on the usage of Wi-Fi signals for human activity detection. A large number of Wi-Fi based sensing systems have been developed, including respiration detection, gesture classification, identity recognition, etc. However, the usability and robustness of such system…	HZ Hualei Zhang et al.Northwestern Polytechnical University
sUrban: Stable Prediction for Unseen Urban Data from Location-based Sensors "Recent machine learning research on smart cities has achieved great success in predicting future trends, under the key assumption that the test data follows the same distribution of the training data. The rapid urbanization, however, makes this assumption challenging to hold in practice. Because new data is emerging…	QW Qianru Wang et al.Northwestern Polytechnical University
AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices "The ubiquity of camera-embedded devices and the advances in deep learning have stimulated various intelligent mobile video applications. These applications often demand on-device processing of video streams to deliver real-time, high-quality services for privacy and robustness concerns. However, the performance of th…	SL Sicong Liu et al.Northwestern Polytechnical University
Genie in the Model: Automatic Generation of Human-in-the-Loop Deep Neural Networks for Mobile Applications "Advances in deep neural networks (DNNs) have fostered a wide spectrum of intelligent mobile applications ranging from voice assistants on smartphones to augmented reality with smart-glasses. To deliver high-quality services, these DNNs should operate on resource-constrained mobile platforms and yield consistent perfo…	YW Yanfei Wang et al.Northwestern Polytechnical University
VPRNet: Voxel-based Efficient and Partial-to-Partial Point Cloud Registration on Mobile Devices With the popularity of embedded devices such as LIDAR sensors and depth cameras, the resulting point clouds become the main data format for representing the 3D world and spawn various smart mobile applications. A key technology for enabling these applications to furnish high-quality services is real-time point cloud r…	ZY Zihao Yin et al.Northwestern Polytechnical University
Task Execution Quality Maximization for Mobile Crowdsourcing in Geo-Social Networks With the rapid development of smart devices and high-quality wireless technologies, mobile crowdsourcing (MCS) has been drawing increasing attention with its great potential in collaboratively completing complicated tasks on a large scale. A key issue toward successful MCS is participant recruitment, where a MCS platf…	LW Liang Wang et al.Northwestern Polytechnical University	Crowds and Collaboration
Human-Machine Cooperative Video Anomaly Detection It is still a challenge to detect anomalous events in video sequences in the field of computer vision due to heavy object occlusions, varying crowded densities and complex situations. To address this, we propose a novel human-machine cooperative approach which uses human feedback on anomaly confirmation to inform and…	FY Fan Yang et al.Northwestern Polytechnical University	Human-AI Collaboration / Images in AI