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Mingyang Ling - IEEE Xplore Author Profile

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Author details

Mingyang Ling

Publications

4

Citations

206

Publications by Year

20192024

Co-Authors:

Jianfei CaiKan ChangBoning ChenShuping DangJiuxiang Gu

Show All Co-Authors (15)

Mingyang Ling

Affiliation

School of Electrical Engineering

Guangxi University

Nanning, China

Publication Topics

Convolutional Neural Network,
Object Detection,
Attention Mechanism,
Bounding Box,
Convolutional Layers,
Detection Accuracy,
Enhancement Method,
External Guidance,
Feature Refinement,
Low-resolution Images,
Potential Features,
Super-resolution

Biography

Mingyang Ling received the B.S. degree in communication engineering from Guangxi University, Nanning, China, in 2020. She is currently working toward the Ph.D. degree with the School of Electrical Engineering, Guangxi University, Nanning, China. Her research interests include image super-resolution, demosaicking, and denoising.(Based on document published on 12 March 2024).

Publications

4

Citations

206

Publications by Year

20192024

Co-Authors:

Jianfei Cai
Kan Chang
Boning Chen
Shuping Dang
Jiuxiang Gu

Show All Co-Authors (15)

Author's Published Works

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Showing 1-4 of 4 results

Conferences (3)

Journals (1)

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Single Year
Mingyang Ling(4)
Kan Chang(3)
Mengyu Yin(2)
Zijian Yuan(2)
Boning Chen(2)
School of Computer and Electronic Information, Guangxi University, Nanning, China(3)
School of Electrical Engineering, Guangxi University, Nanning, China(3)
Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning, China(3)
School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia(2)
School of Electrical, Electronic and Mechanical Engineering, University of Bristol, Bristol, U.K.(1)
2024 International Joint Conference on Neural Networks (IJCNN)(2)
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(1)
IEEE Transactions on Computational Imaging(1)
IEEE(4)
Yokohama, Japan(2)
Long Beach, CA, USA(1)
Convolutional Neural Network(3)
Object Detection(3)
Attention Mechanism(2)
Bounding Box(2)
Convolutional Layers(2)

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Results

A Two-Stage Enhancement Method for Object Detection on Low-Resolution Images

Zijian Yuan;Mingyang Ling;Kan Chang;Mengyu Yin;Minghong Li;Boning Chen

2024 International Joint Conference on Neural Networks (IJCNN)

Year: 2024 | Conference Paper |

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Detecting objects on low-resolution (LR) images is a challenging task, as small structures and details contained in LR images are insufficient. To improve the detection accuracy on LR images, a two-stage enhancement framework is proposed in this paper. In the first stage, a lightweight image super-resolution (SR) sub-network is built by incorporating the external guidance obtained by the detection...Show More

A Two-Stage Enhancement Method for Object Detection on Low-Resolution Images

Zijian Yuan;Mingyang Ling;Kan Chang;Mengyu Yin;Minghong Li;Boning Chen

2024 International Joint Conference on Neural Networks (IJCNN)

Year: 2024 | Conference Paper |

Joint Image and Feature Enhancement for Object Detection under Adverse Weather Conditions

Mengyu Yin;Mingyang Ling;Kan Chang;Zijian Yuan;Qingpao Qin;Boning Chen

2024 International Joint Conference on Neural Networks (IJCNN)

Year: 2024 | Conference Paper |

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Object detection under adverse weather conditions remains a challenging problem to date. To address this problem, a joint image and feature enhancement method called JE-YOLO is proposed. Firstly, a lightweight image enhancement network is used to enhance the low-quality image captured under adverse weather conditions. Secondly, to provide rich information for detection, two detection backbones are...Show More

Joint Image and Feature Enhancement for Object Detection under Adverse Weather Conditions

Mengyu Yin;Mingyang Ling;Kan Chang;Zijian Yuan;Qingpao Qin;Boning Chen

2024 International Joint Conference on Neural Networks (IJCNN)

Year: 2024 | Conference Paper |

PRNet: Pyramid Restoration Network for RAW Image Super-Resolution

Mingyang Ling;Kan Chang;Mengyuan Huang;Hengxin Li;Shuping Dang;Baoxin Li

IEEE Transactions on Computational Imaging

Year: 2024 | Volume: 10 | Journal Article |

Cited by: Papers (4)

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Typically, image super-resolution (SR) methods are applied to the standard RGB (sRGB) images produced by the image signal processing (ISP) pipeline of digital cameras. However, due to error accumulation, low bit depth and the nonlinearity with scene radiance in sRGB images, performing SR on them is sub-optimal. To address this issue, a RAW image SR method called pyramid restoration network (PRNet)...Show More

PRNet: Pyramid Restoration Network for RAW Image Super-Resolution

Mingyang Ling;Kan Chang;Mengyuan Huang;Hengxin Li;Shuping Dang;Baoxin Li

IEEE Transactions on Computational Imaging

Year: 2024 | Volume: 10 | Journal Article |

Scene Graph Generation With External Knowledge and Image Reconstruction

Jiuxiang Gu;Handong Zhao;Zhe Lin;Sheng Li;Jianfei Cai;Mingyang Ling

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2019 | Conference Paper |

Cited by: Papers (202)

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Scene graph generation has received growing attention with the advancements in image understanding tasks such as object detection, attributes and relationship prediction, etc. However, existing datasets are biased in terms of object and relationship labels, or often come with noisy and missing annotations, which makes the development of a reliable scene graph prediction model very challenging. In ...Show More

Scene Graph Generation With External Knowledge and Image Reconstruction

Jiuxiang Gu;Handong Zhao;Zhe Lin;Sheng Li;Jianfei Cai;Mingyang Ling

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2019 | Conference Paper |

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