Lei Zhang
Orcid: 0000-0001-8749-7459Affiliations:
- Nanjing Normal University, School of Electrical and Automation Engineering, China
- Southeast University, School of Instrumental Science and Engineering, Nanjing, China (PhD 2011)
According to our database1,
Lei Zhang
authored at least 44 papers
between 2009 and 2024.
Collaborative distances:
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Bibliography
2024
A Collaborative Compression Scheme for Fast Activity Recognition on Mobile Devices via Global Compression Ratio Decision.
IEEE Trans. Mob. Comput., April, 2024
PatchHAR: A MLP-Like Architecture for Efficient Activity Recognition Using Wearables.
IEEE Trans. Biom. Behav. Identity Sci., April, 2024
Dynamic Inference via Localizing Semantic Intervals in Sensor Data for Budget-Tunable Activity Recognition.
IEEE Trans. Ind. Informatics, March, 2024
An automatic network structure search via channel pruning for accelerating human activity inference on mobile devices.
Expert Syst. Appl., March, 2024
Learn From Others and Be Yourself in Federated Human Activity Recognition via Attention-Based Pairwise Collaborations.
IEEE Trans. Instrum. Meas., 2024
IEEE Access, 2024
2023
Channel Attention for Sensor-Based Activity Recognition: Embedding Features into all Frequencies in DCT Domain.
IEEE Trans. Knowl. Data Eng., December, 2023
FreqSense: Adaptive Sampling Rates for Sensor-Based Human Activity Recognition Under Tunable Computational Budgets.
IEEE J. Biomed. Health Informatics, December, 2023
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., December, 2023
Adversarial Cluster-Level and Global-Level Graph Contrastive Learning for node representation.
Knowl. Based Syst., November, 2023
Toward Effective Personalized Service QoS Prediction From the Perspective of Multi-Task Learning.
IEEE Trans. Netw. Serv. Manag., September, 2023
Channel-Equalization-HAR: A Light-weight Convolutional Neural Network for Wearable Sensor Based Human Activity Recognition.
IEEE Trans. Mob. Comput., September, 2023
ProtoHAR: Prototype Guided Personalized Federated Learning for Human Activity Recognition.
IEEE J. Biomed. Health Informatics, August, 2023
IEEE Trans. Ind. Informatics, March, 2023
An Efficient Diverse-Branch Convolution Scheme for Sensor-Based Human Activity Recognition.
IEEE Trans. Instrum. Meas., 2023
Multiscale Deep Feature Learning for Human Activity Recognition Using Wearable Sensors.
IEEE Trans. Ind. Electron., 2023
Deep Ensemble Learning for Human Activity Recognition Using Wearable Sensors via Filter Activation.
ACM Trans. Embed. Comput. Syst., 2023
Modeling and predicting user preferences with multiple item attributes for sequential recommendations.
Knowl. Based Syst., 2023
Learning hierarchical time series data augmentation invariances via contrastive supervision for human activity recognition.
Knowl. Based Syst., 2023
2022
Mashup-Oriented Web API Recommendation via Multi-Model Fusion and Multi-Task Learning.
IEEE Trans. Serv. Comput., 2022
A lightweight neural network framework using linear grouped convolution for human activity recognition on mobile devices.
J. Supercomput., 2022
Dual-Branch Interactive Networks on Multichannel Time Series for Human Activity Recognition.
IEEE J. Biomed. Health Informatics, 2022
Deformable Convolutional Networks for Multimodal Human Activity Recognition Using Wearable Sensors.
IEEE Trans. Instrum. Meas., 2022
Deep Convolutional Networks With Tunable Speed-Accuracy Tradeoff for Human Activity Recognition Using Wearables.
IEEE Trans. Instrum. Meas., 2022
Understanding and Improving Channel Attention for Human Activity Recognition by Temporal-Aware and Modality-Aware Embedding.
IEEE Trans. Instrum. Meas., 2022
IEEE Trans. Emerg. Top. Comput. Intell., 2022
Human activity recognition using wearable sensors by heterogeneous convolutional neural networks.
Expert Syst. Appl., 2022
Proceedings of the Collaborative Computing: Networking, Applications and Worksharing, 2022
2021
The Convolutional Neural Networks Training With Channel-Selectivity for Human Activity Recognition Based on Sensors.
IEEE J. Biomed. Health Informatics, 2021
Shallow Convolutional Neural Networks for Human Activity Recognition Using Wearable Sensors.
IEEE Trans. Instrum. Meas., 2021
Deep Neural Networks for Sensor-Based Human Activity Recognition Using Selective Kernel Convolution.
IEEE Trans. Instrum. Meas., 2021
Sequential Weakly Labeled Multiactivity Localization and Recognition on Wearable Sensors Using Recurrent Attention Networks.
IEEE Trans. Hum. Mach. Syst., 2021
DanHAR: Dual Attention Network for multimodal human activity recognition using wearable sensors.
Appl. Soft Comput., 2021
2020
DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors.
CoRR, 2020
Real-time Human Activity Recognition Using Conditionally Parametrized Convolutions on Mobile and Wearable Devices.
CoRR, 2020
Efficient convolutional neural networks with smaller filters for human activity recognition using wearable sensors.
CoRR, 2020
Sequential Weakly Labeled Multi-Activity Recognition and Location on Wearable Sensors using Recurrent Attention Network.
CoRR, 2020
2019
Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors.
CoRR, 2019
2016
Adaptive stochastic gradient descent on the Grassmannian for robust low-rank subspace recovery.
IET Signal Process., 2016
2013
Algorithms, 2013
2009
IEEE Geosci. Remote. Sens. Lett., 2009