Tao Lü

Wuhan Institute of Technology

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Yanduo Zhang

Hubei University of Arts and Science

Zhongyuan Wang

Wuhan University

Junjun Jiang

Guangxi Medical University

Jiaming Wang

Wuhan Institute of Technology

Zhen Han

Wuhan University

Zixiang Xiong

CRRC (China)

Ruimin Hu

Wuhan University

Zhenfeng Shao

State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing

Jiayi Ma

Wuhan University

Xiao Huang

Emory University

Cooperative Institutions

Wuhan Institute of Technology

113

Chinese Academy of Sciences

103

Wuhan University

101

University of Chinese Academy of Sciences

Huazhong University of Science and Technology

Peking University

Zhejiang University

Shanghai Jiao Tong University

Tsinghua University

Northwestern Polytechnical University

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Efficient Single Image Super-Resolution via Graph Embedding

Junjun Jiang Ruimin Hu Zhen Han Kebin Huang Tao Lü

We explore in this paper efficient algorithmic solutions to single image super-resolution (SR). We propose the GESR, namely Graph Embedding Super-Resolution, to super-resolve a high-resolution (HR) image from a single low-resolution (LR) observation. The basic idea of GESR is to learn a projection matrix mapping the LR image patch to the HR image patch space while preserving the intrinsic geometrical structure of original HR image patch manifold. While GESR resembles other manifold learning-based SR methods in persevering the local geometric structure of HR and LR image patch manifold, the innovation of GESR lies in that it preserves the intrinsic geometrical structure of original HR image patch manifold rather than LR image patch manifold, which may be contaminated because of image degeneration (e.g., blurring, down-sampling and noise). Experiments on benchmark test images show that GESR can achieve very competitive performance as Neighbor Embedding based SR (NESR) and Sparse representation based SR (SSR). Beyond subjective and objective evaluation, all experiments show that GESR is much faster than both NESR and SSR.

Manifold (fluid mechanics)

Benchmark (surveying)

10.1109/icme.2012.102

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Citations (16)

Water Segmentation via Asymmetric Multiscale Interaction Network

Communications in computer and information science (2023)

Jianzhuo Chen Tao Lü Yanduo Zhang Wenhua Fang Xiya Rao

10.1007/978-981-99-0856-1_16

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Citations (0)

E-government Framework Design Based on Grid Technology

International Conference on Internet Computing and Information Services (2011)

Tao Lü Lin Qin Haitao Lv

In recent years, grid technology is more and more popular to design e-government in domestic and foreign. This paper analyses the characters of grid technology, proposes the framework of e-government based on grid technology, and lists the key problems in implementation.

10.1109/icicis.2011.88

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Citations (1)

Front Matter

Tao Lü Minggao Zhou Yongren Feng Yuqing Yang Wilson C. Chin

The prelims comprise: Half-Title Page Series Page Title Page Copyright Page Contents Preface Acknowledgements

10.1002/9781119760719.fmatter

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Rethinking the Role of Panchromatic Images in Pan-sharpening

IEEE Transactions on Multimedia (2025)

Jiaming Wang Xitong Chen Xiao Huang Ruiqian Zhang Yu Wang

Panchromatic film

Sharpening

10.1109/tmm.2025.3535309

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A patient-driven control method for lower-limb rehabilitation robot

Xiaonan Wang Tao Lü Shijun Wang Jiaojiao Gu Kui Yuan

Lower-limb rehabilitation robots can support the training of patients with neurological gait disorders. Compared to the robot-driven control strategy which permits patients to remain passive during the training, Patient-driven control strategy can motivate the patient's participation and accelerate the rehabilitation process. In this paper, based on a self-developed lower-limb rehabilitation robot, a patient-driven control method is developed and implemented to realize a patient-in-charge gait training strategy. During the training, the proposed control algorithm adapts the motion pattern of the robot according to the estimated patient's voluntary efforts and increases the patient's movement freedom by a certain amount of robot compliance. By adjusting the parameters, the degree of robot compliance can be set based on the patient's voluntary abilities. Experiment results are presented to evaluate the basic principal and technical function of the proposed method and show positive for improving the subject's voluntary contribution during the training.

10.1109/icma.2016.7558683

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Citations (5)

Innovative Teaching Reform of Embedded System Course —Taking Robot Project as Teaching Template

Proceedings of the 2018 3rd International Conference on Education, E-learning and Management Technology (EEMT 2018) (2018)

Xiangjin Zeng Dun-Bo Cai Tao Lü

According to the characteristics and requirements of the embedded industry, this paper explores the innovative teaching mode of embedded system course, which improves the teaching quality and students' interest in learning by designing the teaching content and adopting the project of robot platform.

Course (navigation)

10.2991/iceemt-18.2018.78

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Citations (1)

Efficient low-rank supported extreme learning machine for robust face recognition

Yingjie Guan Tao Lü Yanduo Zhang Bo Wang Xiaolin Li

Recently, deep learning based face recognition algorithms have achieved great success in recognition performance. However, designing and training complex learning models suffer from time and labor efficiency. In this paper, we propose a novel three-layer low-rank supported extreme learning machine (LSELM) algorithm to take advantage of both robust feature representation and fast classification for efficient recognition. Every given probe sample is first clustered into a sub-class spanned by linear representation. With this sub-class, low-rank and robust features that are insensitive to disguise, noise, variant expression or illumination are recovered. These discriminative features are then coded to support a forward neural network for efficient prediction. Experimental results show that LSELM is on par with other deep learning based face recognition algorithms in recognition performance but has less time complexity on both AR and extend Yale-B datasets.

Discriminative model

Extreme Learning Machine

Feature (linguistics)

Rank (graph theory)

Representation

Feature Learning

Robustness

10.1109/vcip.2016.7805436

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Citations (1)

Experimental Research on the Concrete Using Spontaneous Combustion Gangue as Full Active Material

Guisuanyan tongbao (2011)

Tao Lü

The feasibility of fabricating gangue portland cement using spontaneous combusion gangue as full active material is investgated by orthogonal experiments and the concrete with different strength has been prepared by the gangue portland cement,gangue sand and gangue gravel.The results show that the gangue from Fuxin Gaode mine can be used as full active material to fabricate gangue portland cement and the C15-C40 concrete can be produced with the gangue portland cement and gangue coarse and fine aggregates.The 7 d and 28 d strength of the concrete are better than those of normal portland concrete.Moreover,the volume of gangue can reach 80% of total concrete mass.The gangue concrete not only realizes the resource utilization of solid waste but also solves the problem of lack of rigid stone in that location,which has multiple benefit on economic,environmental protecion and society.

Gangue

Source

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Mechanism for Fe(III) to decrease cadmium uptake of wheat plant: Rhizosphere passivation, competitive absorption and physiological regulation

The Science of The Total Environment (2024)

Xianjie Duan Ling Liu Tao Lü Sheliang Wang Chuang Wang

Passivation

10.1016/j.scitotenv.2024.172907

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Citations (1)