Min Zhang

Orcid: 0000-0002-8681-5889

Affiliations:
  • Xidian University, Measurement and Control Department, Xi'an, China


According to our database1, Min Zhang authored at least 31 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
SCM-GNN: A Graph Neural Network-Based Multi-Antenna Spectrum Sensing in Cognitive Radio.
IEEE Trans. Cogn. Commun. Netw., February, 2025

Prototype-Guided Spatial-Spectral Interaction Network for Hyperspectral Anomaly Detection.
IEEE Trans. Geosci. Remote. Sens., 2025

Multiview Graph Neural Networks for Spectrum Sensing in Cognitive Radio.
IEEE Internet Things J., 2025

Modulation recognition method based on multimodal features.
Frontiers Commun. Networks, 2025

2024
Hyperspectral Anomaly Detection via Low-Rank Representation with Dual Graph Regularizations and Adaptive Dictionary.
Remote. Sens., June, 2024

Dynamic Low-Rank and Sparse Priors Constrained Deep Autoencoders for Hyperspectral Anomaly Detection.
IEEE Trans. Instrum. Meas., 2024

Low-Rank and Sparse Representation Inspired Interpretable Network for Hyperspectral Anomaly Detection.
IEEE Trans. Instrum. Meas., 2024

Deep Self-Representation Learning Framework for Hyperspectral Anomaly Detection.
IEEE Trans. Instrum. Meas., 2024

Deep Feature Aggregation Network for Hyperspectral Anomaly Detection.
IEEE Trans. Instrum. Meas., 2024

Memory-Augmented Autoencoder With Adaptive Reconstruction and Sample Attribution Mining for Hyperspectral Anomaly Detection.
IEEE Trans. Geosci. Remote. Sens., 2024

Remote Sensing Image Denoising Based on Feature Interaction Complementary Learning.
Remote. Sens., 2024

SSUM: Spatial-Spectral Unified Mamba for Hyperspectral Image Classification.
Remote. Sens., 2024

2023
Vector Decomposition-Based Arbitrary-Oriented Object Detection for Optical Remote Sensing Images.
Remote. Sens., October, 2023

Hyperspectral Anomaly Detection Using Spatial-Spectral-Based Union Dictionary and Improved Saliency Weight.
Remote. Sens., July, 2023

A combination network of CNN and transformer for interference identification.
Frontiers Comput. Neurosci., February, 2023

Arbitrary-Oriented Ellipse Detector for Ship Detection in Remote Sensing Images.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

Dual Collaborative Constraints Regularized Low-Rank and Sparse Representation via Robust Dictionaries Construction for Hyperspectral Anomaly Detection.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

Hyperspectral Anomaly Detection via Sparse Representation and Collaborative Representation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

Two-Stream Isolation Forest Based on Deep Features for Hyperspectral Anomaly Detection.
IEEE Geosci. Remote. Sens. Lett., 2023

2022
Ship Detection in SAR Images Based on Multi-Scale Feature Extraction and Adaptive Feature Fusion.
Remote. Sens., 2022

Hyperspectral Anomaly Detection via Dual Dictionaries Construction Guided by Two-Stage Complementary Decision.
Remote. Sens., 2022

Ship Detection in SAR Images Based on Feature Enhancement Swin Transformer and Adjacent Feature Fusion.
Remote. Sens., 2022

Multiscale Superpixel Guided Discriminative Forest for Hyperspectral Anomaly Detection.
Remote. Sens., 2022

2021
High-Resolution Time-to-Digital Converters Implemented on 40-, 28-, and 20-nm FPGAs.
IEEE Trans. Instrum. Meas., 2021

Hyperspectral Anomaly Detection via Local Gradient Guidance.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
Precise Frequency Comparison System Using Phase Coincidence Demarcation.
IEEE Trans. Instrum. Meas., 2020

2019
Sensor Fault Detection and Diagnosis Method for AHU Using 1-D CNN and Clustering Analysis.
Comput. Intell. Neurosci., 2019

2018
Flexible, Stretchable Sensors for Wearable Health Monitoring: Sensing Mechanisms, Materials, Fabrication Strategies and Features.
Sensors, 2018

Enhanced Efficiency BPSK Demodulator Based on One-Dimensional Convolutional Neural Network.
IEEE Access, 2018

2017
A 7.4 ps FPGA-Based TDC with a 1024-Unit Measurement Matrix.
Sensors, 2017

Digital-to-Time Converter with 3.93 ps Resolution Implemented on FPGA Chips.
IEEE Access, 2017


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