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arXiv 2019年

作者： Liu, Yuanyuan Peng, Jiyao Zeng, Jiabei Shan, Shiguang School of Geography and Information Engineering China University of Geosciences Wuhan430074 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Key Laboratory of Intelligent Information Processing Center for Excellence in Brain Science and Intelligence Technology Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

Multi-view facial expression recognition (FER) is a challenging task because the appearance of an expression varies in poses. To alleviate the influences of poses, recent methods either perform pose normalization or learn separate FER classifiers for each pose. However, these methods usually have two stages and rely on good performance of pose estimators. Different from existing methods, we propose a pose-adaptive hierarchical attention network (PhaNet) that can jointly recognize the facial expressions and poses in unconstrained environment. Specifically, PhaNet discovers the most relevant regions to the facial expression by an attention mechanism in hierarchical scales, and the most informative scales are then selected to learn the poseinvariant and expression-discriminative representations. PhaNet is end-to-end trainable by minimizing the hierarchical attention losses, the FER loss and pose loss with dynamically learned loss weights. We validate the effectiveness of the proposed PhaNet on three multi-view datasets (BU-3DFE, Multi-pie, and KDEF) and two in-the-wild FER datasets (AffectNet and SFEW). Extensive experiments demonstrate that our framework outperforms the state-of-the-arts under both within-dataset and cross-dataset settings, achieving the average accuracies of 84.92%, 93.53%, 88.5%, 54.82% and 31.25% respectively. Copyright © 2019, The Authors. All rights reserved.

关键词： Face recognition

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Luminescence properties and applications of Ca2ScTaO6: Bi3+, Ln3+ (Ln = Eu, Sm, Dy, Tb) phosphors

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Ceramics International 2025年

作者： Niu, Yaping Wu, Fugen Zhuo, Yifu Li, Jie Zhang, Qi Teng, Yun Xie, Xiaozhu Dong, Huafeng Mu, Zhongfei School of Materials and Energy Guangdong University of Technology Waihuan Xi Road No.100 Guangzhou510006 China The College of Information Engineering Guangzhou Vocational University of Science and Technology Guangcong Nine Road Guangzhou510550 China The School of Information Engineering Guangdong University of Technology Guangzhou510006 China The School of Electronic Engineering Beijing University of Posts and Telecommunications Bejing100876 China Beijing Key Laboratory of Space-Ground Interconnection and Convergence Beijing100876 China Laser Micro/Nano Processing Lab School of Electromechanical Engineering Guangdong University of Technology Guangzhou510006 China School of Physics and Optoelectronic Engineering Guangdong University of Technology Waihuan Xi Road No.100 Guangzhou510006 China Experimental Teaching Department Guangdong University of Technology Waihuan Xi Road No.100 Guangzhou510006 China

Currently, phosphors have been widely used in many fields, such as lighting, display, non-contact optical temperature measurement, color-temperature indicating, anti-counterfeiting, and so on. However, it remains a challenge to develop phosphors with multiple functions. Herein, a series of Ca2ScTaO6 (CSTO): Bi3+, Ln3+ (Ln = Eu, Sm, Dy, Tb) phosphors were synthesized by traditional high-temperature solid-phase method. Under 307 nm excitation, Bi3+ doped CSTO presents broadband emission with a peak at 382 nm in near-ultraviolet (NUV) spectral region. Taking advantage of the different luminous thermal stability of Bi3+ and Ln3+ (Ln = Eu, Sm, Dy, Tb), a series of optical thermometers were evaluated. Among them, CSTO: Bi3+, Eu3+ phosphor presents the best fluorescence temperature sensing performance (Maximums of absolute sensitivity (Sa) and relative sensitivity (Sr) are 0.139 K-1 (398 K) and 1.91 % K−1 (423 K), respectively). Luminescence color of CSTO: Bi3+, Dy3+ phosphor change significantly with increasing temperature, exhibiting their application as a color-temperature indicator. Anti-counterfeiting application of mixed phosphors, CSTO: Eu3+ and CSTO: Bi3+, Tb3+, under excitation at different wavelengths was also demonstrated. These results indicate that CSTO: Bi3+, Ln3+ (Ln = Eu, Sm, Dy, Tb) phosphors are multifunctional with promising applications in the fields of optical temperature measurement, color-temperature indicating, and anti-counterfeiting. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Temperature measurement

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Multiple reconstruction compression framework based on PNG image

arXiv

引用

arXiv 2019年

作者： Lu, Zhiqing Yin, Zhaoxia Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China

It is shown that neural networks (NNs) achieve excellent performances in image compression and reconstruction. However, there are still many shortcomings in the practical application, which eventually lead to the loss of neural network image processing ability. Based on this, this paper proposes a joint framework based on neural network and zoom compression. The framework first encodes the incoming PNG or JPEG image information, and then the image is converted into binary input decoder to reconstruct the intermediate state image, next we import the intermediate state image into the zooming compressor and re-pressurize it, and reconstruct the final image. From the experimental results, this method can better process the digital image and suppress the reverse expansion problem, and the compression effect can be improved by 4 to 10 times as much as that of using RNN alone, showing better ability in application. In this paper, the method is transmitted over a digital image, the effect is far better than the existing compression method alone, the Human visual system can not feel the change of the effect. Copyright © 2019, The Authors. All rights reserved.

关键词： Image compression

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DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Images

arXiv

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arXiv 2023年

作者： Qian, Bo Chen, Hao Wang, Xiangning Che, Haoxuan Kwon, Gitaek Kim, Jaeyoung Choi, Sungjin Shin, Seoyoung Krause, Felix Unterdechler, Markus Hou, Junlin Feng, Rui Li, Yihao Daho, Mostafa El Habib Wu, Qiang Zhang, Ping Yang, Xiaokang Cai, Yiyu Li, Huating Jia, Weiping Sheng, Bin Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Hong Kong Department of Ophthalmology Shanghai Jiao Tong University Affiliated Sixth People’s Hospital Shanghai China VUNO Inc. Seoul Korea Republic of AI/DX Convergence Business Group KT Korea Republic of Johannes Kepler University Linz Linz Austria School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Fudan University China Academy for Engineering and Technology Fudan University China LaTIM UMR 1101 Inserm Brest France University of Western Brittany Brest France Department of Computer Science and Engineering The Ohio State University Ohio United States Department of Biomedical Informatics The Ohio State University Ohio United States Translational Data Analytics Institute The Ohio State University Ohio United States MoE Key Lab of Artificial Intelligence Artificial Intelligence Institute Shanghai Jiao Tong University Shanghai China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Department of Endocrinology and Metabolism Shanghai Jiao Tong University Affiliated Sixth People’s Hospital Shanghai China Shanghai Diabetes Institute Shanghai Clinical Center for Diabetes Shanghai China

Computer-assisted automatic analysis of diabetic retinopathy (DR) is of great importance in reducing the risks of vision loss and even blindness. Ultra-wide optical coherence tomography angiography (UW-OCTA) is a non-invasive and safe imaging modality in DR diagnosis system, but there is a lack of publicly available benchmarks for model development and evaluation. To promote further research and scientific benchmarking for diabetic retinopathy analysis using UW-OCTA images, we organized a challenge named "DRAC - Diabetic Retinopathy Analysis Challenge" in conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022). The challenge consists of three tasks: segmentation of DR lesions, image quality assessment and DR grading. The scientific community responded positively to the challenge, with 11, 12, and 13 teams from geographically diverse institutes submitting different solutions in these three tasks, respectively. This paper presents a summary and analysis of the top-performing solutions and results for each task of the challenge. The obtained results from top algorithms indicate the importance of data augmentation, model architecture and ensemble of networks in improving the performance of deep learning models. These findings have the potential to enable new developments in diabetic retinopathy analysis. The challenge remains open for post-challenge registrations and submissions for benchmarking future methodology developments. Copyright © 2023, The Authors. All rights reserved.

关键词： Optical tomography

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Impulse control of chaos in the exible shaft rotating-lifting system of the mono-silicon crystal puller

arXiv

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arXiv 2020年

作者： Zhou, Zi-Xuan Grebogi, Celso Ren, Hai-Peng Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an Shaanxi710048 China North Minzu University Library Yinchuan Ningxia750021 China Institute for Complex System and Mathematical Biology University of Aberdeen AB24 3UE United Kingdom

Chaos is shown to occur in the flexible shaft rotating-lifting (FSRL) system of the mono-silicon crystal puller. Chaos is, however, harmful for the quality of mono-silicon crystal production. Therefore, it should be suppressed. Many chaos control methods have been proposed theoretically and some have even been used in applications. For a practical plant displaying harmful chaos, engineers from a specified area usually face with the challenge to identifying chaos and to suppressing it by using a proper method. However, despite of the existing methods, chaos control method selection in the FSRL system is not a trivial task. For example, for the OGY method, if one cannot find a practical adjustable parameter, then the OGY method cannot be applied. An impulsive control method is being proposed which is efficiently able to suppress chaos in the FSRL system. The selection of the control parameters is obtained by using the Melnikov method. Simulation results show the correctness of our theoretical analysis and the effectiveness of the proposed chaos control method. Copyright © 2020, The Authors. All rights reserved.

关键词： Silicon

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An Improved Switching Controller for Boost Converter Based on Hybrid Automata Model

An Improved Switching Controller for Boost Converter Based o...

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Chinese Automation Congress (CAC)

作者： Yi-Juan Ning Hai-Peng Ren Jie Li Shaanxi Key Laboratory of CoTplex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China Department of Electrical Engineering Xi’an University of Technology Xi’an China

Power electronic converters play an important role in the energy conversion. Power electronic converters, exhibiting different system dynamical characteristics according to the onoff state of the switch, are typical switching (nonlinear) systems. The traditional model of power electronic converter is the small signal average model and the converter controller is designed using the linear system theory. This kind of method is effective only within the vicinity of the predefined operating point. When the system parameter varies in a large scale, the converter control performance will degrade. The hybrid system model reflects the essential switching characteristics of the converter, and the controllers designed based on the hybrid model are suitable for converter control when the system states or parameters vary in a large scale. However, the parameter uncertainty is still a problem in conventional switching control method. In this paper, the inductor current compensation control is proposed to deal with the uncertainties of the circuit parameters and working point variation. The effectiveness of the proposed method is verified by both simulation and experiment.

关键词： Switches Voltage control Resistance Inductance Matrix converters

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Cyber-physical model for efficient and secured operation of CPES or energy Internet

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Science China(information Sciences) 2018年第11期61卷 5-7页

作者： Xiaohong GUAN Zhanbo XU Qing-Shan JIA Kun LIU Yadong ZHOU Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Center for Intelligent and Networked Systems Department of AutomationBeijing National Research Center for Information Science and Technology (BNRist) Tsinghua University

Dear editor,Global energy and environmental crisis is one of the most serious issues on the sustainable development of human society in the 21st century. Making full use of renewable energy sources is one of the most effective ways to resolve the energy and environmental problems. However, we are facing the serious challenges due to the uncertain natures of the renewable energy sources.

关键词： In

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Adaptive Clustering SOFC Image Segmentation Based on Particle Swarm Optimization

Adaptive Clustering SOFC Image Segmentation Based on Particl...

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2019 3rd International Conference on Machine Vision and information technology (CMVIT 2019)

作者： Xuefei Yang Xiaowei Fu Xi Li College of Computer Science and Technology Wuhan University of Science and TechnologyHubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System State Key Laboratory of Materials Processing and Die & Mould Technology Huazhong University of Science and Technology College of Automation Huazhong University of Science and Technology

Microstructural parameters are important for analyzing the chemistry and performance of solid oxide fuel cells（SOFCs）. Aiming at the YSZ/Ni anode optical microscopy（OM） image of SOFC, in this paper, particle swarm intelligent optimization algorithm is used to improve the fuzzy C-means clustering algorithm for image segmentation. Particle swarm optimization is used to adaptively search the initial clustering center, helping to avoid local optimization and preserve more image detail. The experimental results show that the proposed method can improve the segmentation accuracy of images. At the same time, it can accurately segment the SOFC three-phase and provide effective image segmentation results for the microstructure parameters.

关键词：

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Investigating Bi-level optimization for learning and vision from a unified perspective: A survey and beyond

arXiv

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arXiv 2021年

作者： Liu, Risheng Gao, Jiaxin Zhang, Jin Meng, Deyu Lin, Zhouchen DUT-RU International School of Information Science & Engineering Dalian University of Technology Key Laboratory for Ubiquitous Network Service Software of Liaoning Province Dalian116024 China Department of Mathematics Southern University of Science and Technology National Center for Applied Mathematics Shenzhen China School of Mathematics and Statistics Ministry of Education Key Lab of Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an Shaanxi China School of Electronics Engineering and Computer Science Peking University Beijing100871 China Cooperative Medianet Innovation Center Shanghai Jiao Tong University Shanghai200240 China

Bi-Level Optimization (BLO) is originated from the area of economic game theory and then introduced into the optimization community. BLO is able to handle problems with a hierarchical structure, involving two levels of optimization tasks, where one task is nested inside the other. In machine learning and computer vision fields, despite the different motivations and mechanisms, a lot of complex problems, such as hyper-parameter optimization, multi-task and meta learning, neural architecture search, adversarial learning and deep reinforcement learning, actually all contain a series of closely related subproblms. In this paper, we first uniformly express these complex learning and vision problems from the perspective of BLO. Then we construct a best-response-based single-level reformulation and establish a unified algorithmic framework to understand and formulate mainstream gradient-based BLO methodologies, covering aspects ranging from fundamental automatic differentiation schemes to various accelerations, simplifications, extensions and their convergence and complexity properties. Last but not least, we discuss the potentials of our unified BLO framework for designing new algorithms and point out some promising directions for future research. © 2021, CC BY.

关键词： Deep learning

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ZSTAD: Zero-shot temporal activity detection

arXiv

引用

arXiv 2020年

作者： Zhang, Lingling Chang, Xiaojun Liu, Jun Luo, Minnan Wang, Sen Ge, Zongyuan Hauptmann, Alexander School of Computer Science and Technology Xian Jiaotong University Xian China Ministry of Education Key Lab For Intelligent Networks and Network Security Xian China Faculty of Information Technology Monash University Australia National Engineering Lab for Big Data Analytics Xian Jiaotong University Xian China School of Information Technology and Electrical Engineering University of Queensland Australia School of Computer Science Carnegie Mellon University United States

An integral part of video analysis and surveillance is temporal activity detection, which means to simultaneously recognize and localize activities in long untrimmed videos. Currently, the most effective methods of temporal activity detection are based on deep learning, and they typically perform very well with large scale annotated videos for training. However, these methods are limited in real applications due to the unavailable videos about certain activity classes and the time-consuming data annotation. To solve this challenging problem, we propose a novel task setting called zero-shot temporal activity detection (ZSTAD), where activities that have never been seen in training can still be detected. We design an end-to-end deep network based on R-C3D as the architecture for this solution. The proposed network is optimized with an innovative loss function that considers the embeddings of activity labels and their super-classes while learning the common semantics of seen and unseen activities. Experiments on both the THUMOS14 and the Charades datasets show promising performance in terms of detecting unseen activities. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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