检索结果-内蒙古大学图书馆

IEEE International Conference on Image Processing

作者： Zibin He Tao Dai Jian Lu Yong Jiang Shu-Tao Xia Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Convolutional neural networks (CNNs) have been widely used in image super-resolution (SR). Most existing CNN-based methods focus on achieving better performance by designing deeper/wider networks, while suffering from heavy computational cost problem, thus hindering the deployment of such models in mobile devices with limited resources. To relieve such problem, we propose a novel and efficient SR model, named Feature Affinity-based Knowledge Distillation (FAKD), by transferring the structural knowledge of a heavy teacher model to a lightweight student model. To transfer the structural knowledge effectively, FAKD aims to distill the second-order statistical information from feature maps and trains a lightweight student network with low computational and memory cost. Experimental results demonstrate the efficacy of our method and the effectiveness over other knowledge distillation based methods in terms of both quantitative and visual metrics.

关键词： Knowledge engineering Computational modeling Correlation Image resolution Task analysis Feature extraction Mathematical model

来源：评论

学校读者我要写书评

暂无评论

A practical framework for automatic 3D reconstruction of clothing with RGB-D cameras

A practical framework for automatic 3D reconstruction of clo...

引用

2019 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2019

作者： Chang, Hongguang Song, Zhan Zhao, Juan Shenzhen College of Advanced Technology University of Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781728137261

Accurate 3D modelling of real clothing is of great significance for many applications. However, most existing methods of acquiring these 3D models are too expensive and non-automatic. In this paper, we propose a practical framework for the automatic 3D reconstruction of clothing by scanning real clothes using a motorized rotation stage and three RGB-D cameras (Intel RealSense Depth Camera D415). The framework consists of three parts, including data acquisition module, point cloud process module and model reconstruction module. Users can easily use it to reconstruct clothes because it works automatically and quickly. Experimental results show that the proposed system and method can obtain 3D models of clothing with satisfied 3D mesh and texture. This research provides manufacturers a fast and economical way to create 3D clothing models for applications like virtual reality display and online shopping etc. © 2018 IEEE

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Interface optimization and defects suppression via Na F introduction enable efficient flexible Sb_(2)Se_(3) thin-film solar cells

引用

Journal of Energy Chemistry 2024年第3期90卷 165-175,I0006页

作者： Mingdong Chen Muhammad Ishaq Donglou Ren Hongli Ma Zhenghua Su Ping Fan David Le Coq Xianghua Zhang Guangxing Liang Shuo Chen Shenzhen Key Laboratory of Advanced Thin Films and Applications Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong ProvinceCollege of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060GuangdongChina State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures MOE Key Laboratory of New Processing Technology for Nonferrous Metals and MaterialsSchool of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004GuangxiChina CNRS ISCR(Institut des Sciences Chimiques de Rennes)UMR 6226Universitéde RennesRennes F-35000France

Sb_(2)Se_(3) with unique one-dimensional(1D) crystal structure exhibits exceptional deformation tolerance,demonstrating great application potential in flexible ***,the power conversion efficiency(PCE) of flexible Sb_(2)Se_(3) photovoltaic devices is temporarily limited by the complicated intrinsic defects and the undesirable contact ***,a high-quality Sb_(2)Se_(3) absorber layer with large crystal grains and benign [hkl] growth orientation can be first prepared on a Mo foil *** NaF intermediate layer is introduced between Mo and Sb_(2)Se_(3),which can further optimize the growth of Sb_(2)Se_(3)thin ***,positive Na ion diffusion enables it to dramatically lower barrier height at the back contact interface and passivate harmful defects at both bulk and *** a result,the champion substrate structured Mo-foil/Mo/NaF/Sb_(2)Se_(3)/CdS/ITO/Ag flexible thin-film solar cell delivers an obviously higher efficiency of 8.03% and a record open-circuit voltage(V_(OC)) of 0.492 *** flexible Sb_(2)Se_(3) device also exhibits excellent stability and flexibility to stand large bending radius and multiple bending times,as well as superior weak light photo-response with derived efficiency of 12.60%.This work presents an effective strategy to enhance the flexible Sb_(2)Se_(3) device performance and expand its potential photovoltaic applications.

关键词： Sb_(2)Se_(3) Flexible solar cells NaF intermediate layer Interface optimization Defects suppression

来源：评论

学校读者我要写书评

暂无评论

A novel soft exosuit based on biomechanical analysis for assisting lower extremity 22

A novel soft exosuit based on biomechanical analysis for ass...

引用

22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Liu, Youfu Chen, Chunjie Lu, Jun Liu, Yida Zhang, Yu Wang, Zhuo College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shenzhen China ShenZhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (纸本)9781728162676

In the past two decades, with growing focus of lower limb exoskeleton, large variety of rigid exoskeletons were designed for medical rehabilitation and the other purposes. Compared with the rigid exoskeletons, which added extra inertial to low limb and restricted wearers' movement, the soft wearable lower extremity exoskeleton minimized the impact of these factors on the human body locomotion. In this paper, a novel design of exosuit that provided assistive force for both hip extension and flexion through the variation in hip joint dynamics during strides was proposed. Based on the change of hip moment, an assistance strategy and assistance force curve were came up with. PD type iterative learning control (ILC) method was introduced to reduce the error caused by wearing position and biological characteristics to improve assistance performance. To evaluate assistance performance, the metabolic cost of four subjects wearing exosuit and walking on treadmill at 5km/h in the situations of that without assistance, assisting both hip extension and hip flexion, and assisting hip extension respectively was measured. Compared with assisting hip extension only and wearing exosuit with no assistance, results indicated that the decrease in average net metabolic cost of assisting both hip extension and flexion was 0.445W/kg and 1.027W/kg respectively, corresponding to the average net metabolic cost rate decrease was 7.45% and 15.67%. © 2021 IEEE.

关键词： Exoskeleton (Robotics)

来源：评论

学校读者我要写书评

暂无评论

Underwater Image Enhancement via Multi-color Space Correction and Fusion

Underwater Image Enhancement via Multi-color Space Correctio...

引用

Electronic Information Engineering and Computer Technology (EIECT), International Conference on

作者： Chenyu Zhou Bo Chen Ying Zhang Wensheng Chen Binbin Pan Jing Ji Shenzhen Key Laboratory of Advanced Machine Learning and Applications College of Mathematics and Statistics Shenzhen University Shenzhen China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

Underwater image enhancement, as an important branch of image processing, has attracted the attention of many scholars in recent years. Due to selective scattering and degradation of light in water, images captured underwater are generally of low quality. To improve the accuracy of underwater image details and color, we propose a novel underwater image enhancement model, which is based on a Multi-color space fusion (MSF) strategy and assigns corresponding weights to each color channel for fusion. Qualitative and quantitative comparisons show that the proposed method can effectively remove image blur, achieve color correction, and significantly improve image sharpness.

关键词：

来源：评论

学校读者我要写书评

暂无评论

BLOCKS OF THE CATEGORY Op IN TYPE E

arXiv

引用

arXiv 2020年

作者： Jieren, Hu Xiao, Wei Zhang, Ailin College of Computer Science and Software Engineering Shenzhen University ShenzhenGuangdong518060 China College of Mathematics and statistics Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen Guangdong518060 China College of Mathematics and statistics Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen Guangdong518060 China

关键词：

来源：评论

学校读者我要写书评

暂无评论

Review of machine-vision-based plant detection technologies for robotic weeding

Review of machine-vision-based plant detection technologies ...

引用

2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Li, Nan Zhang, Xiaoguang Zhang, Chunlong Ge, Luzhen He, Yong Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China Shenzhen University Shenzhen518060 China China Agricultural University College of Engineering Beijing100083 China

ISBN: (纸本)9781728163215

Controlling weeds with reduced reliance on herbicides is one of the main challenges to move toward a more sustainable agriculture. Robotic weeding is a thought to be a viable way to reduce the environmental loading of agrochemicals while keeping the operation efficiency high. One of the key technologies for performing robotic weeding is automatic detection of crops and weeds in fields. This paper presents an overview on various methods for detecting plants based on machine vision, mainly concentrating on two main challenges: dealing with changing light and crop/weed discrimination. To overcome the first challenge, both physical and algorithmic methods have been proposed. Physical methods can result in a more cumbersome machine while algorithmic methods are less robust. For crop/weed discrimination, deep-learning-based methods have shown obvious advantages over traditional methods based on hand-crafted features. However, traditional methods still hold some merits that can be leveraged to deep-learning-based methods. With the fast development of hardware technologies, researchers should take full advantage of advanced hardware to ease the algorithm design. In the future, the identification of crops and weeds can be more accurate and fine-grained with the support of online databases and computing resources based on the advances in artificial intelligence and communication technologies. © 2019 IEEE.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

RuO_(2) clusters derived from bulk SrRuO_(3):Robust catalyst for oxygen evolution reaction in acid

引用

Nano Research 2022年第3期15卷 1959-1965页

作者： Muwei Ji Xin Yang Shengding Chang Wenxing Chen Jin Wang Dongsheng He Yao Hu Qian Deng You Sun Bo Li Jingyu Xi Tomoaki Yamada Jiatao Zhang Hai Xiao Caizhen Zhu Jia Li Yadong Li College of Materials Science and Engineering Shenzhen UniversityShenzhen 518060China Institute of Low-Dimensional Materials Genome Initiative College of Chemistry and Environmental Engineering of Shenzhen UniversityShenzhen 518060China Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Beijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Materials Characterization and Preparation Center Southern University of Science and TechnologyShenzhen 518055China Department of Energy Engineering Nagoya UniversityFuro-choChikusa-kuNagoya 464-8603Japan Department of Chemistry Tsinghua UniversityBeijing 100084China

Developing highly efficient oxygen evolution reaction(OER)catalyst for the acidic corrosive operating conditions is a challenging ***,we report the synthesis of uniform RuO_(2)clusters with~2 nm in size via electrochemical leaching of Sr from SrRuO_(3) ceramic in *** RuO_(2)clusters exhibit ultrahigh OER activity with overpotential of~160 mV at 10 mA·cm_(geo)^(−2) in 1.0 M HClO4 solution for 30-h *** extended X-ray absorption fine structure measurement reveals enlarged Jahn-Teller distortion of Ru-O octahedra in the RuO_(2)clusters compared to its bulk *** function theory calculations show that the enhanced Jahn-Teller distortion can improve the intrinsic OER activity of RuO_(2).

关键词： oxygen evolution reaction RuO_(2)cluster electrochemical leaching acid solution

来源：评论

学校读者我要写书评

暂无评论

Donor strategy for promoting nonradiative decay to achieve an efficient photothermal therapy for treating cancer

引用

Science China Chemistry 2021年第9期64卷 1530-1539页

作者： Fei Ren Zeshun Li Kai Li Xiaoyan Zheng Jianbing Shi Chen Zhang Heng Guo Bin Tong Lei Xi Zhengxu Cai Yuping Dong Beijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications School of Materials Science&EngineeringBeijing Institute of TechnologyBeijing100081China Shenzhen Key Laboratory of Smart Healthcare Engineering Department of Biomedical EngineeringSouthern University of Science and Technology(SUSTech)Shenzhen518055China Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials Key Laboratory of Cluster Science of Ministry of EducationSchool of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing100081China

Photothermal therapy(PTT)is emerging as an effective treatment for superficial carcinoma.A key challenge to the effectiveness of PTT is to develop photosensitizers with high photothermal conversion *** to address this challenge,we develop a series of multi-arylpyrrole derivatives with different donors that contain different multi-rotor structures to explore highly efficient PTT *** these multi-arylpyrrole derivatives,MAP4-FE nanoparticles with a small size of their donor groups and better-donating ability exhibit a high photothermal conversion efficiency(up to 72%)when they are encapsulated by an amphiphilic *** a result,the MAP4-FE nanoparticles have shown satisfactory PTTeffects on in vivo tumor eradication under the guidance of photoacoustic *** findings of this study provide significant insights for the development of high-efficiency PTT photosensitizers for cancer treatment by making full use of the nonradiative decay of small size donors as rotors.

关键词： aggregation-induced emission multi-arylpyrroles photothermal therapy photoacoustic imaging

来源：评论

学校读者我要写书评

暂无评论

Deep Grouped Non-Negative Matrix Factorization Method for Image Data Representation

Deep Grouped Non-Negative Matrix Factorization Method for Im...

引用

International Conference on machine learning and Cybernetics (ICMLC)

作者： Zihao Zhan Wen-Sheng Chen Binbin Pan Bo Chen College of Mathematics and Statistics Shenzhen University China Guangdong Key Laboratory of Media Security Shenzhen University China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University China

ISBN: (纸本)9781665466097

Non-negative matrix factorization (NMF) is an unsupervised learning method that can be exploited for parts-based image representation due to non-negativity constraints. However, singer-layer NMF cannot capture the latent hierarchical structure features from images, while deep features play more important roles in the image representation and recognition tasks. To overcome the limitation of NMF, this paper proposes a novel deep grouped NMF (DGNMF) approach to learn different level attributes of the data. It is interesting that DGNMF approach automatically makes the data from distinct classes share different basis images and the feature vectors among different classes are mutually orthogonal at the same layer. Meanwhile, to preserve the local information, our DGNMF model establishes the objective function with graph regularization, and its optimization problem is solved using gradient descent method. The developed DGNMF algorithm is proved to be convergent and is finally evaluated on face datasets for classification. Compared with some state-of-the-art deep NMF variants, the results demonstrate the proposed DGNMF algorithm achieves surpassing performances using different layer features.

关键词： machine learning algorithms Face recognition machine learning Image representation Classification algorithms Matrix decomposition Task analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：