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2nd International Conference on Mechatronics and Industrial Informatics, ICMII 2014

作者： Wang, Yue Lin, Zeng Gang Liao, Zi Cheng Shaanxi Provincial Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University China

ISBN: (纸本)9783038351764

In this paper a new No-Reference (NR) image quality assessment (IQA) method based on the point wise statistics of local normalized luminance signals using region of interest (ROI) processing is proposed. This algorithm firstly extracts the ROI which is relative to human subjectivity by using the image gradient and phase congruency, and then extracts the image quality feature in spatial domain. Particularly, most of the present IQA methods mainly focus on predicting the image quality with respect to human perception, yet, in some other image domains, the final receiver of a digital image may not a human. Thus, we propose a method which can assess the image quality relative to edge detection algorithm. In addition, experimental results on LIVE database are provided to justify the superior compared to the significant image quality metrics. © (2014) Trans Tech Publications, Switzerland.

关键词： image quality

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An image quality assessment algorithm based on feature selection

An image quality assessment algorithm based on feature selec...

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3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012

作者： Lu, Ting Zhang, Yanning Li, Haisen Shaanxi Provincial Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University China

ISBN: (纸本)9783642366680

image Quality Assessment(IQA) is of fundamental importance to numerous imaging and video processing applications. For most of the applications, the perceptual meaningful measure is the one which can automatically assess the quality of images or videos in a perceptually consistent manner. However, most commonly used IQA metrics are not consistent well with the human judgments of image quality. Recently, the SSIM metric which takes people's visual characteristics into consideration performs much better than the traditional PSNR/MSE. But the defects of it still exit on some specific kinds of distortions. A new algorithm of IQA based on feature selection is proposed in this paper. Local gradient entropy and phase congruency are added to the SSIM framework. Through in-depth feature selection and definition plus better pooling strategy, this algorithm performs much better in LIVE datasets. © Springer-Verlag 2013.

关键词： Entropy

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Road Crack Acquisition and Analysis System Based on Mobile Robot and Deep Learning 11

Road Crack Acquisition and Analysis System Based on Mobile R...

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11th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021

作者： Zhu, Guijie Fan, Zhun Ma, Peili Huang, Wenning Ye, Zhihao Huang, Mingwei Li, Jiangli Jiang, Zhicheng Zhong, Zhuwei He, Weiyuan Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou515063 China

ISBN: (纸本)9781665425278

In this paper, a road crack acquisition and analysis system based on mobile robot and deep learning is proposed. First, a virtual reality technology-based omnidirectional mobile robot is developed to remotely collect detailed road crack images. Next, an image dataset including different kinds of crack images collected by the mobile robot is constructed and utilized for training and testing a deep convolutional neural network (DCNN) model. Following this, the trained model is used to identify and segment the crack images acquired from the robot, and to facilitate the inspector to know the road surface condition, crack information (crack length, crack width, and crack area) is obtained using an image processing method. Finally, the proposed system and method are applied to a campus road, which realizes the accurate acquisition and analysis of road crack information, thus demonstrating the feasibility and effectiveness of the proposed system and method. © 2021 IEEE.

关键词： Mobile robots

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Enhancing Deep Learning-based Depression Level Estimation Based on Multi-task Learning 24

Enhancing Deep Learning-based Depression Level Estimation Ba...

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7th International Conference on Machine Learning and Machine Intelligence, MLMI 2024

作者： Ye, Qingxin Xie, Zhenming Sun, Hao Xin, Luyao Chen, Youwen Song, Jian Chen, Yen-Wei Provincial key Laboratory of Computational Science Huaqiao University Quanzhou China Intelligent Image Processing Lab Zhejiang University Hangzhou China Intelligent Image Processing Lab Ritsumeikan University Osaka Japan

ISBN: (纸本)9798400717833

In recent years, depression, as a serious mental illness, has received widespread attention from various sectors of society. How to identify depressive emotions in a timely manner and detect depression has become an urgent issue that needs to be addressed. Currently, many experts and scholars propose using deep learning methods to assess the level of depression. Compared to other deep learning models, Transformer models have parallel computing capabilities with their self-attention mechanism, enabling them to handle entire sequences and capture long-distance dependencies. After the success of Transformers in natural language processing, similar architectures have been introduced into the field of computer vision, promoting advancements in multi-modal research. However, how to integrate other information or tasks to improve assessment accuracy remains a challenge. In our team's preliminary work, we proposed a multi-modal adaptive fusion Transformer network for assessing depression levels. Inspired by multi-task learning, we introduced gender classification as a second auxiliary task alongside the main task of depression regression, forming a three-task learning framework including depression classification. This was done to enhance the model's performance. We validated the effectiveness of the proposed method by testing it on a public dataset (AVEC 2019 Detecting Depression with AI Sub-challenge). The experimental results show that our proposed method achieved a Concordance Correlation Coefficient (CCC) of 0.60448, which is 1.688% higher than the accuracy of the dual-task learning method (CCC = 0.5876). © 2024 Copyright held by the owner/author(s).

关键词： Multi-task learning

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A WYNER-ZIV VIDEO CODING METHOD UTILIZING MIXTURE CORRELATION NOISE MODEL

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Journal of Electronics(China) 2012年第3期29卷 197-203页

作者： Hu Xiaofei Zhu Xiuchang Image Processing and Image Communication Key Laboratory Nanjing University of Posts and Telecommunications Nanjing 210003 China College of Geography and Biological Information Nanjing University of Posts and Telecommunications Nanjing 210003 China

In Wyner-Ziv (WZ) Distributed Video Coding (DVC), correlation noise model is often used to describe the error distribution between WZ frame and the side information. The accuracy of the model can influence the performance of the video coder directly. A mixture correlation noise model in Discrete Cosine Transform (DCT) domain for WZ video coding is established in this paper. Different correlation noise estimation method is used for direct current and alternating current coefficients. Parameter estimation method based on expectation maximization algorithm is used to estimate the Laplace distribution center of direct current frequency band and Mixture Laplace-Uniform Distribution Model (MLUDM) is established for alternating current coefficients. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the noise model presented by DIStributed COding for Video sERvices (DISCOVER).

关键词： Transform domain Wyner-Ziv (WZ) DIStributed COding for Video sERvices (DISCOVER) Video coding Correlation noise model Mixture Laplace-Uniform Distribution Model (MLUDM)

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A Survey on Negative Transfer

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 305-329页

作者： Wen Zhang Lingfei Deng Lei Zhang Dongrui Wu the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China IEEE the School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China

Transfer learning(TL)utilizes data or knowledge from one or more source domains to facilitate learning in a target *** is particularly useful when the target domain has very few or no labeled data,due to annotation expense,privacy concerns,***,the effectiveness of TL is not always *** transfer(NT),i.e.,leveraging source domain data/knowledge undesirably reduces learning performance in the target domain,and has been a long-standing and challenging problem in *** approaches have been proposed in the literature to address this ***,there does not exist a systematic *** paper fills this gap,by first introducing the definition of NT and its causes,and reviewing over fifty representative approaches for overcoming NT,which fall into three categories:domain similarity estimation,safe transfer,and NT *** areas,including computer vision,bioinformatics,natural language processing,recommender systems,and robotics,that use NT mitigation strategies to facilitate positive transfers,are also ***,we give guidelines on NT task construction and baseline algorithms,benchmark existing TL and NT mitigation approaches on three NT-specific datasets,and point out challenges and future research *** ensure reproducibility,our code is publicized at https://***/chamwen/NT-Benchmark.

关键词： Domain adaptation domain similarity negative transfer positive transfer transfer learning

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Multi-view synthesis using the relative affine structure from video sequences

Multi-view synthesis using the relative affine structure fro...

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International Conference on Multimedia and Signal processing (CMSP)

作者： Huo, Zhiyong Liu, Tianliang Zhu, Xiuchang Jiangsu Key Laboratory of Image Processing and Communication Nanjing Univ. of Posts and Telecommun. Nanjing China

ISBN: (纸本)9780769543567

This paper proposes an approach for Multi-view synthesis, the process of view synthesis based on the relative affine structure. We specifying the virtual camera position in an uncalibrated setting, based on the interpolation of the motion among the reference views. Novel images can be rendered from virtual cameras moving on parametric trajectories. Synthetic and real experiments illustrate the approach. © 2011 IEEE.

关键词： Cameras

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3D face recognition based on principal axes registration and fusing features

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Frontiers of Electrical and Electronic Engineering in China 2011年第2期6卷 347-352页

作者： Hongxia ZHANG Yanning ZHANG Zhe GUO Zenggang LIN Chao ZHANG Shaanxi Provincial Key Laboratory of Speech and Image Information Processing(SAIIP) School of Computer ScienceNorthwestern Polytechnical UniversityXi’an 710129China

A 3D face recognition approach which uses principal axes registration(PAR)and three face representation features from the re-sampling depth image:Eigenfaces,Fisherfaces and Zernike moments is *** approach addresses the issue of 3D face registration instantly achieved by *** each facial feature has its own advantages,limitations and scope of use,different features will complement each *** the fusing features can learn more expressive characterizations than a single *** support vector machine(SVM)is applied for *** this method,based on the complementarity between different features,weighted decision-level fusion makes the recognition system have certain fault *** results show that the proposed approach achieves superior performance with the rank-1 recognition rate of 98.36%for GavabDB database.

关键词： 3D face recognition principal axes registration(PAR) fusion feature weighted voting

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Current spin polarization of a platform molecule with compression effect

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Chinese Physics B 2022年第7期31卷 498-504页

作者： Zhi Yang Feng Sun Deng-Hui Chen Zi-Qun Wang Chuan-Kui Wang Zong-Liang Li Shuai Qiu Shandong Key Laboratory of Medical Physics and Image Processing&Shandong Provincial Engineering and Technical Center of Light Manipulations School of Physics and ElectronicsShandong Normal UniversityJinan 250358China Zao Zhuang University Zao Zhuang 277160China

Using the first-principles method,the spin-dependent transport properties of a novel platform molecule containing a freestanding molecular wire is investigated by simulating the spin-polarized scanning tunneling microscope experiment with Ni tip and Au substrate *** calculations show that the total current increases as the tip gradually approaches to the substrate,which is consistent with the conductance obtained from previous *** interestingly,the spin polarization(SP)of current modulated by compression effect has the completely opposite trend to the total *** analyses reveal that the reduction of SP of current with compression process originates from the promotion of spin-down electron channel,which is controlled by deforming the molecule *** addition,the density of states shows that the SP of current is directly affected by the organic–ferromagnetic *** weak orbital hybridization between the Ni tip and propynyl of molecule results in high interfacial SP,whereas the breaking of the C≡C triple of propynyl in favor of the Ni–C–C bond induces the strong orbital hybridization and restrains the interfacial *** work proposes a new way to control and design the SP of current through organic–ferromagnetic spinterface using functional molecular platform.

关键词： molecular spintronics spin-dependent transport spin polarization single-molecule junctions

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A hierarchical diffusion algorithm for community detection in social networks

A hierarchical diffusion algorithm for community detection i...

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International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery

作者： Shen, keyi Song, Li Yang, Xiaokang Zhang, Wenjun Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiao Tong University China

ISBN: (纸本)9780769542355

Community discovery is one of the most important steps to understand the social networks. We propose a hierarchical diffusion method to detect the community structure. Our algorithm is based on the idea that people in different communities usually share less common friends. We also make use of the fact that people usually make decisions based others' choices, especially their friends'. Our algorithm can distinguish between pseudo-communities and meaningful ones. Tests on both classical and synthetic benchmarks show that our algorithm is comparable to state-of-the-art community detection algorithms in both computational complexity and accuracy measured by the so-called normalized mutual information. © 2010 IEEE.

关键词： Diffusion

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