Jun Zhang
Orcid: 0000-0003-1321-6022Affiliations:
- Chinese Academy of Sciences, Hefei Institutes of Physical Science, High Magnetic Field Laboratory, China
- University of Science and Technology of China, Hefei, China
According to our database1,
Jun Zhang
authored at least 20 papers
between 2017 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2023
FPT: Fine-Grained Detection of Driver Distraction Based on the Feature Pyramid Vision Transformer.
IEEE Trans. Intell. Transp. Syst., February, 2023
YOLOv4-dense: A smaller and faster YOLOv4 for real-time edge-device based object detection in traffic scene.
IET Image Process., February, 2023
IEEE Trans. Intell. Transp. Syst., 2023
2022
Learning Accurate, Speedy, Lightweight CNNs via Instance-Specific Multi-Teacher Knowledge Distillation for Distracted Driver Posture Identification.
IEEE Trans. Intell. Transp. Syst., 2022
A New Unsupervised Deep Learning Algorithm for Fine-Grained Detection of Driver Distraction.
IEEE Trans. Intell. Transp. Syst., 2022
Pattern Recognit., 2022
Circuits Syst. Signal Process., 2022
Multi-Path Siamese Convolution Network for Offline Handwritten Signature Verification.
Proceedings of the ICCDE 2022: The 8th International Conference on Computing and Data Engineering, Bangkok, Thailand, January 11, 2022
2021
Contextual similarity-based multi-level second-order attention network for semi-supervised few-shot learning.
Neurocomputing, 2021
Multi-Scale Spatial Temporal Graph Neural Network for Skeleton-Based Action Recognition.
IEEE Access, 2021
2020
LGSim: local task-invariant and global task-specific similarity for few-shot classification.
Neural Comput. Appl., 2020
IEEE Access, 2020
2019
Driving Safety Risk Prediction Using Cost-Sensitive With Nonnegativity-Constrained Autoencoders Based on Imbalanced Naturalistic Driving Data.
IEEE Trans. Intell. Transp. Syst., 2019
A Deep Learning Framework for Driving Behavior Identification on In-Vehicle CAN-BUS Sensor Data.
Sensors, 2019
Mutual information-based dropout: Learning deep relevant feature representation architectures.
Neurocomputing, 2019
Driver identification based on hidden feature extraction by using adaptive nonnegativity-constrained autoencoder.
Appl. Soft Comput., 2019
Attention-Based Convolutional and Recurrent Neural Networks for Driving Behavior Recognition Using Smartphone Sensor Data.
IEEE Access, 2019
2018
Cross-covariance regularized autoencoders for nonredundant sparse feature representation.
Neurocomputing, 2018
2017
Neural Comput. Appl., 2017