Xing Hu

Orcid: 0000-0003-1930-0372

Affiliations:
  • University of Shanghai for Science and Technology, School of Optical-Electrical and Computer Engineering, China


According to our database1, Xing Hu authored at least 29 papers between 2016 and 2025.

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Bibliography

2025
Dictionary trained attention constrained low rank and sparse autoencoder for hyperspectral anomaly detection.
Neural Networks, 2025

2024
Open-set marine object instance segmentation with prototype learning.
Signal Image Video Process., September, 2024

TFF-CNN: Distributed optical fiber sensing intrusion detection framework based on two-dimensional multi-features.
Neurocomputing, January, 2024

Open Set Intrusion Event Recognition Using Anchor Point Learning for Distributed Optical Fiber System.
IEEE Trans. Instrum. Meas., 2024

2023
Build a bridge between ECG and EEG signals for atrial fibrillation diagnosis using AI methods.
Comput. Biol. Medicine, November, 2023

A novel cell contour-based instance segmentation model and its applications in HER2 breast cancer discrimination.
Biomed. Signal Process. Control., August, 2023

Residual spatial graph convolution and temporal sequence attention network for sign language translation.
Multim. Tools Appl., June, 2023

Spatial-Temporal Graph Convolutional Network Boosted Flow-Frame Prediction For Video Anomaly Detection.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Comprehensive Review of Deep Learning-Based 3D Point Cloud Completion Processing and Analysis.
IEEE Trans. Intell. Transp. Syst., 2022

Video anomaly detection based on 3D convolutional auto-encoder.
Signal Image Video Process., 2022

Unsupervised Learning of Monocular Depth and Ego-Motion with Optical Flow Features and Multiple Constraints.
Sensors, 2022

Hyperspectral Anomaly Detection Using Deep Learning: A Review.
Remote. Sens., 2022

TOP-ALCM: A novel video analysis method for violence detection in crowded scenes.
Inf. Sci., 2022

Networking Systems of AI: On the Convergence of Computing and Communications.
IEEE Internet Things J., 2022

A deep learning based 2-dimensional hip pressure signals analysis method for sitting posture recognition.
Biomed. Signal Process. Control., 2022

PG-YOLO: A Novel Lightweight Object Detection Method for Edge Devices in Industrial Internet of Things.
IEEE Access, 2022

A Deep Learning-Based Method for Drivers' Shoe-Wearing Recognition.
Proceedings of the Sensor Systems and Software - 13th EAI International Conference, 2022

HFF-Net: Hierarchical Feature Fusion Network for Point Cloud Generation with Point Transformers.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2022

2021
Improved human action recognition approach based on two-stream convolutional neural network model.
Vis. Comput., 2021

Learning Optical Flow with R-CNN for Visual Odometry.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Stack Multiple Shallow Autoencoders into a Strong One: A New Reconstruction-Based Method to Detect Anomaly.
Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020
Temporal Tensor Local Binary Pattern: A Novel Local Tensor Time Series Descriptor.
IEEE Trans. Ind. Informatics, 2020

A weakly supervised framework for abnormal behavior detection and localization in crowded scenes.
Neurocomputing, 2020

An enhanced adaptive non-local means algorithm for Rician noise reduction in magnetic resonance brain images.
BMC Medical Imaging, 2020

2019
Squirrel-Cage Local Binary Pattern and Its Application in Video Anomaly Detection.
IEEE Trans. Inf. Forensics Secur., 2019

An Anti-occlusion and Scale Adaptive Kernel Correlation Filter for Visual Object Tracking.
KSII Trans. Internet Inf. Syst., 2019

2018
Lane Detection Based on Inverse Perspective Transformation and Kalman Filter.
KSII Trans. Internet Inf. Syst., 2018

Abnormal event detection in crowded scenes using histogram of oriented contextual gradient descriptor.
EURASIP J. Adv. Signal Process., 2018

2016
Video anomaly detection using deep incremental slow feature analysis network.
IET Comput. Vis., 2016


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