Hanling Zhang - IEEE Xplore Author Profile
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Hanling Zhang

Also published under: HanLing Zhang

Publications
13
Citations
171
Publications by Year
20142024
Co-Authors:
Show All Co-Authors (29)
Image of author Hanling Zhang

Hanling Zhang

Also published under: HanLing Zhang

Affiliation

School of Design
Hunan University
Changsha, China

Publication Topics

Biography

Hanling Zhang received the master’s degree from Central South University in 1999, and the Ph.D. degree from Northwestern Polytechnical University in 2003. He is a Professor with the School of Information Science and Engineering, Hunan University, China. He has published more than 70 papers in international journals and conferences. His research interests include image processing and computer vision.(Based on document published on 21 April 2021).
Publications
13
Citations
171
Publications by Year
20142024
Co-Authors:
Show All Co-Authors (29)
Author's Published Works

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Hyperspectral Image Denoising via $L_{0}$ Regularized Low-Rank Tucker Decomposition

Xin Tian;Kun Xie;Hanling Zhang

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2024 | Volume: 17 | Journal Article |
Cited by: Papers (1)
This article studies the mixed noise removal problem for hyperspectral images (HSIs), which often suffer from Gaussian noise and sparse noise. Conventional denoising models mainly employ the $L_{1}$-norm-based regularizers to remove sparse noise and ensure piecewise smoothness. However, the denoising performance is poor for highly structured images with severe noise since the $L_{1}$-norm overpena...Show More

Hyperspectral Image Denoising via $L_{0}$ Regularized Low-Rank Tucker Decomposition

Xin Tian;Kun Xie;Hanling Zhang

Year: 2024 | Volume: 17 | Journal Article |

A Study of Smart Home User Personas Based on Context Theory

Yingbo Luo;Hanling Zhang

2022 8th International HCI and UX Conference in Indonesia (CHIuXiD)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
To achieve a safe, convenient, comfortable, and environmentally friendly home life experience, smart home field has reached a new stage of development, where actively providing user-centered service is crucial. Therefore, it needs to capture the real needs of users in different contexts accurately. This study proposes a theoretical method and structural model of user personas construction in the f...Show More

A Study of Smart Home User Personas Based on Context Theory

Yingbo Luo;Hanling Zhang

Year: 2022 | Volume: 1 | Conference Paper |

HDNet: Multi-Modality Hierarchy-Aware Decision Network for RGB-D Salient Object Detection

Chengxing Xia;Songsong Duan;Bin Ge;Hanling Zhang;Kuan-Ching Li

IEEE Signal Processing Letters
Year: 2022 | Volume: 29 | Journal Article |
Cited by: Papers (6)
RGB-D Salient object detection (SOD) is a pixel-level dense prediction task, which can highlight the prominent object in the scene. Recently, Convolution Neural Network (CNN) is widely applied in SOD to generate multi-level features, which are complementary to each other. However, most methods ignore the unique characteristics of multi-level features (high-level and low-level features). Given the ...Show More

HDNet: Multi-Modality Hierarchy-Aware Decision Network for RGB-D Salient Object Detection

Chengxing Xia;Songsong Duan;Bin Ge;Hanling Zhang;Kuan-Ching Li

Year: 2022 | Volume: 29 | Journal Article |

Multi-Modality Diversity Fusion Network with Swintransformer for RGB-D Salient Object Detection

Songsong Duan;Chenxing Xia;Xiuju Gao;Bin Ge;Hanling Zhang;Kuan-Ching Li

2022 IEEE International Conference on Image Processing (ICIP)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
Multi-modality complementary information brings new impetus and innovation to saliency object detection (SOD). However, most existing RGB-D SOD methods either indiscriminately handle RGB features and depth features or only take depth features as additional information of RGB subnet-work, ignoring the different roles of two modalities for SOD tasks. To tackle this issue, we propose a novel multi-mo...Show More

Multi-Modality Diversity Fusion Network with Swintransformer for RGB-D Salient Object Detection

Songsong Duan;Chenxing Xia;Xiuju Gao;Bin Ge;Hanling Zhang;Kuan-Ching Li

Year: 2022 | Conference Paper |

Emcenet: Efficient Multi-Scale Context Exploration Network for Salient Object Detection

Yanguang Sun;Chenxing Xia;Xiuju Gao;Bin Ge;Hanling Zhang;Kuan-Ching Li

2022 IEEE International Conference on Image Processing (ICIP)
Year: 2022 | Conference Paper |
Multi-scale context is crucial for the accurate salient object detection (SOD) in the real-world scenes. Although current contextual information-based SOD methods have achieved great progress, they may fail to generate precise saliency maps due to their seldom considering the correlation of different scale context during the extraction process. To address these issues, we propose an Efficient Mult...Show More

Emcenet: Efficient Multi-Scale Context Exploration Network for Salient Object Detection

Yanguang Sun;Chenxing Xia;Xiuju Gao;Bin Ge;Hanling Zhang;Kuan-Ching Li

Year: 2022 | Conference Paper |

A Review of Micro-expression Recognition based on Deep Learning

He Zhang;Hanling Zhang

2022 International Joint Conference on Neural Networks (IJCNN)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
Micro-expression has the characteristics of spontaneity, low intensity, and short duration, which reflects a real personal emotion. Therefore, micro-expression recognition (MER) has been applied widely in lie detection, depression analysis, human-computer interaction systems, and commercial negotiation. Micro-expressions usually occur when people attempt to cover up their true feelings, especially...Show More

A Review of Micro-expression Recognition based on Deep Learning

He Zhang;Hanling Zhang

Year: 2022 | Conference Paper |

A Low-Rank Tensor Decomposition Model With Factors Prior and Total Variation for Impulsive Noise Removal

Xin Tian;Kun Xie;Hanling Zhang

IEEE Transactions on Image Processing
Year: 2022 | Volume: 31 | Journal Article |
Cited by: Papers (8)
Image restoration is a long-standing problem in signal processing and low-level computer vision. Previous studies have shown that imposing a low-rank Tucker decomposition (TKD) constraint could produce impressive performances. However, the TKD-based schemes may lead to the overfitting/underfitting problem because of incorrectly predefined ranks. To address this issue, we prove that the $n$ -rank ...Show More

A Low-Rank Tensor Decomposition Model With Factors Prior and Total Variation for Impulsive Noise Removal

Xin Tian;Kun Xie;Hanling Zhang

Year: 2022 | Volume: 31 | Journal Article |

Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild

Zhaoyuan Yin;Jia Zheng;Weixin Luo;Shenhan Qian;Hanling Zhang;Shenghua Gao

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2021 | Conference Paper |
Cited by: Papers (12)
This paper proposes a framework for the interactive video object segmentation (VOS) in the wild where users can choose some frames for annotations iteratively. Then, based on the user annotations, a segmentation algorithm refines the masks. The previous interactive VOS paradigm selects the frame with some worst evaluation metric, and the ground truth is required for calculating the evaluation metr...Show More

Learning to Recommend Frame for Interactive Video Object Segmentation in the Wild

Zhaoyuan Yin;Jia Zheng;Weixin Luo;Shenhan Qian;Hanling Zhang;Shenghua Gao

Year: 2021 | Conference Paper |

Early Intra CU Size Decision for Versatile Video Coding Based on a Tunable Decision Model

Yue Li;Gaobo Yang;Yun Song;Hanling Zhang;Xiangling Ding;Dengyong Zhang

IEEE Transactions on Broadcasting
Year: 2021 | Volume: 67, Issue: 3 | Journal Article |
Cited by: Papers (51)
Versatile video coding (VVC) further improves video coding gain by introducing a new Quad-tree (QT) with nested multi-type tree (QTMT) partition structure, which includes QT partition, horizontal and vertical binary-tree (BT) partition, and horizontal and vertical ternary-tree (TT) partition. However, the coding gain is achieved at the cost of drastically increased coding complexity. We propose an...Show More

Early Intra CU Size Decision for Versatile Video Coding Based on a Tunable Decision Model

Yue Li;Gaobo Yang;Yun Song;Hanling Zhang;Xiangling Ding;Dengyong Zhang

Year: 2021 | Volume: 67, Issue: 3 | Journal Article |

Multi-Scale Convolutional Neural Networks for Scene Recognition

Zheng Yi;HanLing Zhang

2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
Year: 2019 | Conference Paper |
In recent years, convolutional neural network (CNN) has performed well in a number of image classification tasks, but it hit a bottleneck on scene recognition task, due to the multilevel semantic information in a scene. This paper is dedicated to studying the deep learning methods in scene recognition task, and making contributes to improving the classification performance in the field of scene re...Show More

Multi-Scale Convolutional Neural Networks for Scene Recognition

Zheng Yi;HanLing Zhang

Year: 2019 | Conference Paper |

Unsupervised Salient Object Detection by Aggregating Multi-Level Cues

Chenxing Xia;Hanling Zhang

IEEE Photonics Journal
Year: 2018 | Volume: 10, Issue: 6 | Journal Article |
Cited by: Papers (5)
In this paper, we present a novel method to detect salient object based on multi-level cues. First, a proposal processing scheme is developed by various object-level saliency cues to generate an initial saliency map. For the sake of more accurate object boundaries, a two-stage optimization mechanism is then proposed upon superpixel-level. Finally, the superpixel-level saliency map is further impro...Show More

Unsupervised Salient Object Detection by Aggregating Multi-Level Cues

Chenxing Xia;Hanling Zhang

Year: 2018 | Volume: 10, Issue: 6 | Journal Article |

Mining Mid-Level Features for Action Recognition Based on Effective Skeleton Representation

Pichao Wang;Wanqing Li;Philip Ogunbona;Zhimin Gao;Hanling Zhang

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
Year: 2014 | Conference Paper |
Cited by: Papers (30)
Recently, mid-level features have shown promising performance in computer vision. Mid-level features learned by incorporating class-level information are potentially more discriminative than traditional low-level local features. In this paper, an effective method is proposed to extract mid-level features from Kinect skeletons for 3D human action recognition. Firstly, the orientations of limbs conn...Show More

Mining Mid-Level Features for Action Recognition Based on Effective Skeleton Representation

Pichao Wang;Wanqing Li;Philip Ogunbona;Zhimin Gao;Hanling Zhang

Year: 2014 | Conference Paper |

Discriminative Key Pose Extraction Using Extended LC-KSVD for Action Recognition

Lijuan Zhou;Wanqing Li;Yuyao Zhang;Philip Ogunbona;Duc Thanh Nguyen;Hanling Zhang

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
Year: 2014 | Conference Paper |
Cited by: Papers (52)
This paper presents a method for extracting discriminative key poses for skeleton-based action recognition. Poses are represented by normalized joint locations, velocities and accelerations of skeleton joints. An extended label consistent K-SVD (ELC-KSVD) algorithm is proposed for learning the common and action-specific dictionaries. Discriminative key poses are represented by the atoms of the act...Show More

Discriminative Key Pose Extraction Using Extended LC-KSVD for Action Recognition

Lijuan Zhou;Wanqing Li;Yuyao Zhang;Philip Ogunbona;Duc Thanh Nguyen;Hanling Zhang

Year: 2014 | Conference Paper |

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