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Chaoyun Mai - IEEE Xplore Author Profile

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Author details

Chaoyun Mai

Publications

6

Citations

58

Publications by Year

20172024

Co-Authors:

Zhenfeng BaiRuggero Donida LabatiJunying GanAngelo GenoveseGuohui He

Show All Co-Authors (25)

Chaoyun Mai

Affiliation

School of Electronics and Information Engineering

Wuyi University

Jiangmen, Guangdong, China

Publication Topics

Deep Learning,
Feature Maps,
Convolutional Neural Network,
Source Domain,
Transfer Learning,
Unmanned Aerial Vehicles,
Ablation Experiments,
Adaptive Modulation,
Amount Of Annotated Data,
Angle Measurements,
Antenna Parameters,
Aspect Ratio

Biography

Chaoyun Mai received the Ph.D. degree in information and communication engineering from Beihang University, Beijing, China, in 2017.,He is currently Associate Professor with the School of Electronics and Information Engineering, Wuyi University, Guangdong, China. His current research interests include image processing and signal processing.(Based on document published on 19 March 2024).

Publications

6

Citations

58

Publications by Year

20172024

Co-Authors:

Zhenfeng Bai
Ruggero Donida Labati
Junying Gan
Angelo Genovese
Guohui He

Show All Co-Authors (25)

Author's Published Works

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Showing 1-6 of 6 results

Journals (5)

Conferences (1)

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Chaoyun Mai(6)
Yikui Zhai(4)
Fabio Scotti(4)
Vincenzo Piuri(4)
Ruggero Donida Labati(3)
Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China(3)
Departimento di Information, Universita Degli Studi di Milano, Milan, Italy(2)
School of Electronic and Information Engineering, Beihang University, Beijing, China(2)
School of Information and Engineering, Wuyi University, Jiangmen, China(2)
Lite-On Singapore, Singapore(1)
IEEE Access(2)
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)(1)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing(1)
IEEE Transactions on Geoscience and Remote Sensing(1)
IEEE Transactions on Instrumentation and Measurement(1)
IEEE(6)
Shanghai, China(1)
Deep Learning(3)
Feature Maps(3)
Convolutional Neural Network(2)
Optimization Problem(2)
Power Spectral Density(2)

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DBCG-Net: Dual Branch Calibration Guided Deep Network for UAV Images Semantic Segmentation

Chaoyun Mai;Yibo Wu;Yikui Zhai;Hao Quan;Jianhong Zhou;Angelo Genovese;Vincenzo Piuri;Fabio Scotti

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2024 | Volume: 17 | Journal Article |

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Unmanned aerial vehicle (UAV) remote sensing images used for semantic segmentation possess distinct features compared to urban street scene images, including high resolution and a complex background. Spatial information plays a pivotal role in enhancing the performance of semantic segmentation for high-resolution images. The dual-branch architecture for semantic segmentation incorporates supplemen...Show More

DBCG-Net: Dual Branch Calibration Guided Deep Network for UAV Images Semantic Segmentation

Chaoyun Mai;Yibo Wu;Yikui Zhai;Hao Quan;Jianhong Zhou;Angelo Genovese;Vincenzo Piuri;Fabio Scotti

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2024 | Volume: 17 | Journal Article |

A³PNet: Antijam and Accurate Antenna Parameters Measuring Network for Mobile Communication Base Station Using UAV

Yikui Zhai;Ziyi Jiang;Chaoyun Mai;Jinrui Liao;Wenqi Wang;Junying Zeng;Chuanbo Qin;Ruggero Donida Labati;Vincenzo Piuri;Fabio Scotti

IEEE Transactions on Instrumentation and Measurement

Year: 2022 | Volume: 71 | Journal Article |

Cited by: Papers (2)

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Whether the down-tilt angle of the mobile communication base station antenna is reasonable directly affects the coverage effect and communication quality of the whole network. Measurement of traditional antenna parameters mainly relies on engineers climbing the base station for manual measurements, confronting the dilemma of low measurement efficiency and a dangerous working environment. Moreover,...Show More

A³PNet: Antijam and Accurate Antenna Parameters Measuring Network for Mobile Communication Base Station Using UAV

Yikui Zhai;Ziyi Jiang;Chaoyun Mai;Jinrui Liao;Wenqi Wang;Junying Zeng;Chuanbo Qin;Ruggero Donida Labati;Vincenzo Piuri;Fabio Scotti

IEEE Transactions on Instrumentation and Measurement

Year: 2022 | Volume: 71 | Journal Article |

Weakly Contrastive Learning via Batch Instance Discrimination and Feature Clustering for Small Sample SAR ATR

Yikui Zhai;Wenlve Zhou;Bing Sun;Jingwen Li;Qirui Ke;Zilu Ying;Junying Gan;Chaoyun Mai;Ruggero Donida Labati;Vincenzo Piuri;Fabio Scotti

IEEE Transactions on Geoscience and Remote Sensing

Year: 2022 | Volume: 60 | Journal Article |

Cited by: Papers (13)

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In recent years, impressive performance of deep learning technology has been recognized in synthetic aperture radar (SAR) automatic target recognition (ATR). Since a large amount of annotated data are required in this technique, it poses a trenchant challenge to the issue of obtaining a high recognition rate through less labeled data. To overcome this problem, inspired by the contrastive learning,...Show More

Weakly Contrastive Learning via Batch Instance Discrimination and Feature Clustering for Small Sample SAR ATR

Yikui Zhai;Wenlve Zhou;Bing Sun;Jingwen Li;Qirui Ke;Zilu Ying;Junying Gan;Chaoyun Mai;Ruggero Donida Labati;Vincenzo Piuri;Fabio Scotti

IEEE Transactions on Geoscience and Remote Sensing

Year: 2022 | Volume: 60 | Journal Article |

2M BeautyNet: Facial Beauty Prediction Based on Multi-Task Transfer Learning

Junying Gan;Li Xiang;Yikui Zhai;Chaoyun Mai;Guohui He;Junying Zeng;Zhenfeng Bai;Ruggero Donida Labati;Vincenzo Piuri;Fabio Scotti

Year: 2020 | Volume: 8 | Journal Article |

Cited by: Papers (19)

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Facial beauty prediction (FBP) has become an emerging area in the field of artificial intelligence. However, the lacks of data and accurate face representation hinder the development of FBP. Multi-task transfer learning can effectively avoid over-fitting, and utilize auxiliary information of related tasks to optimize the main task. In this paper, we present a network named Multi-input Multi-task B...Show More

2M BeautyNet: Facial Beauty Prediction Based on Multi-Task Transfer Learning

Junying Gan;Li Xiang;Yikui Zhai;Chaoyun Mai;Guohui He;Junying Zeng;Zhenfeng Bai;Ruggero Donida Labati;Vincenzo Piuri;Fabio Scotti

Year: 2020 | Volume: 8 | Journal Article |

Complementary Codes Approach to Sparse Frequency Waveform Design

Chaoyun Mai;Guohua Wang;Jinping Sun

2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)

Year: 2018 | Conference Paper |

Cited by: Papers (5)

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Sparse frequency waveform (SFW) is able to utilize spectrums from disjoint channels in a single waveform so as to improve the overall bandwidth that is desirable in both radar and communications. One challenge faced with sparse frequency waveform design is the relatively high range sidelobe level due to spectrum discontinuity. In this paper, a new approach to sparse frequency waveform design with ...Show More

Complementary Codes Approach to Sparse Frequency Waveform Design

Chaoyun Mai;Guohua Wang;Jinping Sun

2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)

Year: 2018 | Conference Paper |

Beampattern Optimization for Frequency Diverse Array With Sparse Frequency Waveforms

Chaoyun Mai;Songtao Lu;Jinping Sun;Guohua Wang

Year: 2017 | Volume: 5 | Journal Article |

Cited by: Papers (19)

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Multiple-input multiple-output (MIMO) radar equipped with a frequency diverse array (FDA) can produce a range-dependent beampattern and increase the degrees-of-freedom of the antenna array. In this paper, a new method of designing the MIMO radar beampattern with sparse frequency waveforms is proposed for the FDA, which randomly samples multiple distance points such that the MIMO radar beampattern ...Show More

Beampattern Optimization for Frequency Diverse Array With Sparse Frequency Waveforms

Chaoyun Mai;Songtao Lu;Jinping Sun;Guohua Wang

Year: 2017 | Volume: 5 | Journal Article |

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