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7th International Conference on information Science and Control Engineering, ICISCE 2020

作者： Meng, Fanchen Zhang, Tianxu Wuhan Institute of Technology Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781728164069

Image recognition has always been an important research topic in the field of pattern recognition. This article uses the printed character recognition of bills as the research background. Through the detailed analysis of the recognition process, some preprocessing algorithms are selected and implemented, including image enhancement, binarization, filtering, character cutting, skew correction, etc. Finally, transplant each algorithm to the simulation platform, mainly for BP algorithm, according to the characteristics of DSP, optimize from two aspects of compilation options and source code to meet the requirements of fast processing. Finally, the requirements of better recognition effect and fast processing speed are realized. © 2020 IEEE.

关键词： Image enhancement

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Machine learning application to predict the electron temperature on the J-TEXT tokamak

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Plasma Science and Technology 2021年第8期23卷 47-52页

作者： Jiaolong DONG Jianchao LI Yonghua DING Xiaoqing ZHANG Nengchao WANG Da LI Wei YAN Chengshuo SHEN Ying HE Xiehang REN Donghui XIA International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and TechnologySchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People's Republic of China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205People's Republic of China

The reliability of diagnostic systems in tokamak plasma is of great significance for physics researches or fusion *** some diagnostics fail to detect information about the plasma status,such as electron temperature,they can also be obtained by another method:fitted by other diagnostic signals through machine *** paper herein is based on a machine learning method to predict electron temperature,in case the diagnostic systems fail to detect plasma *** fully-connected neural network,utilizing back propagation with two hidden layers,is utilized to estimate plasma electron temperature approximately on the *** input parameters consist of soft x-ray emission intensity,electron density,plasma current,loop voltage,and toroidal magnetic field,while the targets are signals of electron temperature from electron cyclotron emission and x-ray imaging crystal ***,the temperature profile is reconstructed by other diagnostic signals,and the average errors are within 5%.In addition,generalized regression neural network can also achieve this function to estimate the temperature profile with similar *** electron temperature by neural network reveals that machine learning can be used as backup means for plasma information so as to enhance the reliability of diagnostics.

关键词： neural network plasma electron temperature J-TEXT tokamak

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Synthesis,Structure and Elastic Properties of a New Hybrid Perovskite Material:[C6H14N2]KBr3

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Chinese Journal of Structural Chemistry 2020年第1期39卷 174-181,6页

作者： Muhammad Azeem ZHANG Hong JI Li-Jun DONG Li-Yuan LU Pei-Xiang LI Wei School of Physics and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205China School of Materials Science and Engineering Nankai UniversityTianjin 300350China

A new hybrid organic-inorganic perovskite(HOIP)material,[C6H14N2]KBr3,has been synthesized via hydrothermal method and fully characterized.[C6H14N2]KBr3 has a three-dimensional perovskite structure and crystalizes in a trigonal P3121 space *** elastic properties of[C6H14N2]KBr3 were fully calculated via the density functional theory calculations,which reveal the elastic moduli(11.54~14.07 GPa),shear moduli(4.56~5.68 GPa),Poisson’s ratios(0.18~0.32),bulk modulus(8.51 GPa)and acoustic velocity(2.57~2.74 kms^-1).Additional nanoindentation experiments in the form of single-crystals confirmed the validity of our theoretical approach.[C6H14N2]KBr3 exhibits higher stiffness and thermal stability than the well-known photovoltaic CH3NH3PbI3,which makes it worthwhile for exploring optoelectronic properties.

关键词： hybrid perovskite density functional theory elastic properties acoustic velocity nanoindentation

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A study on soft x-ray spectra from pulsed 1 μm Nd:YAG laser-induced ytterbium plasmas

A study on soft x-ray spectra from pulsed 1 μm Nd:YAG laser...

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作者： Wu, Tao He, Jun Yang, Li Lu, Peixiang Hubei Key Laboratory Optical Information and Pattern Recognition School of Optical Information and Energy Engineering Wuhan Institute of Technology Wuhan430205 China Guangdong Intelligent Robotics Institute Dongguan523808 China

The Nd:YAG laser with a wavelength of 1.064 μm was used to generate plasmas on a high-purity solid ytterbium (70Yb) target in a vacuum chamber. The soft x-ray time- and space-integration spectra from the Yb plasmas were measured in the wavelength range of 1.0-8.5 nm under different power densities. The atomic spectral data of the unresolved transition arrays from highly charged Yb ions were calculated based on Cowan's suite of codes, including configuration interaction. The calculated Gaussian envelope of the emission determined by the weighted spontaneous transition rates was compared with the experimental spectra, and a good agreement between them was obtained. The spatial-temporal evolutions of the plasmas under the experimental conditions are simulated based on the collisional-radiative model, enabling the understanding of the mechanism of the plasma conditions for optimal water window waveband emission output. © 2020 Hefei Institutes of Physical Science, Chinese Academy of Sciences and IOP Publishing.

关键词： Yttrium aluminum garnet

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Helicity-dependent time delays in multiphoton ionization by two-color circularly polarized laser fields

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Frontiers of physics 2021年第5期16卷 3-9页

作者： Qing-Hua Ke Yue-Ming Zhou Yi-Jie Liao Jin-Tai Liang Yong Zhao Jia Tan Min Li Pei-Xiang Lu School of Physics and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan430205China CAS Center for Excellence in Ultra-intense Laser Science Shanghai201800China

By numerically solving the three-dimensional time-dependent Schrödinger equation,we have investigated multiphoton ionization of hydrogen atom in the two-color circularly polarized(TCCP)laser fields consisting of a strong 400 nm and a much weaker 800 nm *** to the presence of perturbative 800 nm laser pulse,sideband peaks emerge between the above-threshold ionization rings in the photoelectron momentum *** numerical results show that the sideband peaks exhibit one-lobe structure in the co-rotating TCCP laser fields,while it displays the three-lobe structure in the counter-rotating TCCP laser ***,the photoelectron yield of sidebands in the co-rotating TCCP fields is much higher than those of the counter-rotating TCCP *** phenomena could be well explained from the perspective of the photon-absorption channels via the selection ***,an obvious phase shift between the sidebands of different orders from the co-rotating and counter-rotating TCCP fields is *** shift indicates the helicity-dependent time delay in the one-photon continuum-continuum transition process.

关键词： helicity-dependent time delay TCCP multiphoton ionization

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Unveiling Nonsecular Collisional Dissipation of Molecular Alignment

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Physical Review Letters 2024年第3期133卷 033202-033202页

作者： Pu Wang Lixin He Yu Deng Siqi Sun Pengfei Lan Peixiang Lu and School of Physics Hubei Optical Fundamental Research Center Wuhan 430074 China Hubei Key Laboratory of Optical Information and Pattern Recognition

We conducted a joint theoretical and experimental study to investigate the collisional dissipation of molecular alignment. By comparing experimental measurements to the quantum simulations, the nonsecular effect in the collision dissipation of molecular alignment was unveiled from the gas-density-dependent decay rates of the molecular alignment revival signals. Different from the conventional perspective that the nonsecular collisional effect rapidly fades within the initial few picoseconds following laser excitation, our simulations of the time-dependent decoherence process demonstrated that this effect can last for tens of picoseconds in the low-pressure regime. This extended timescale allows for the distinct identification of the nonsecular effect from molecular alignment signals. Our findings present the pioneering evidence that nonsecular molecular collisional dissipation can endure over an extended temporal span, challenging established concepts and strengthening our understanding of molecular dynamics within dissipative environments.

关键词： Atomic & molecular processes in external fields Rotational states

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TCPNet: A 3D Point Cloud Classification Model Based on the Advanced CNN and Transformer 3

TCPNet: A 3D Point Cloud Classification Model Based on the A...

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3rd International Conference on Artificial Intelligence and Computer information Technology, AICIT 2024

作者： Wu, Jinmeng Ma, Jingwei Hong, Hanyu Hao, Yanbin Ma, Lei Wang, Lei Wuhan Institute of Technology Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan China School of Information Science and Technology University of Science and Technology of China Anhui China

ISBN: (纸本)9798350365443

Transformer and Convolutional Neural Network (CNN) are currently two important models in the field of deep learning. Among them, Transformer has strong global perception ability but weak local perception ability, and CNN precisely compensates for this. CNN has strong local perception ability, so in order to combine the advantages of both, we propose a 3D classification model TCPNet based on Transformer and CNN. We first use Transformer to extract the global features of the point cloud, and then concatenate a CNN network to enhance the detail perception ability, so that the network can better understand the 3D point cloud. The experimental results on the ModelNet40 and ScanObjectNN datasets show that our method can effectively achieve 3D classification tasks. On ModelNet40, an accuracy of 93.6% can be achieved. On the most difficult variant PB-T50-RS of ScanObjectNN, an accuracy of 83.93% can be achieved. © 2024 IEEE.

关键词： Convolutional neural networks

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Attention-guided Unsupervised Semantic Fusion for Infrared and Visible Images 15

Attention-guided Unsupervised Semantic Fusion for Infrared a...

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15th International Conference on Graphics and Image Processing, ICGIP 2023

作者： Qi, Qian Kong, Quan Liao, Qing Hu, Ziming Li, Jinglei Zhang, Jialian Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology University China School of Art & Design Wuhan Institute of Technology University China

ISBN: (纸本)9781510675018

Infrared and visible image fusion aims to synthesize a new image with complementary information of the source images such as the thermal radiation information and detailed texture information. However, the existing methods applied in the image fusion tasks tend to pay more attention to the improvements of visual quality and multiple evaluation indicators, while ignoring the importance of semantic information in high-level missions of image processing. In this paper, we present a novel approach to image fusion, where the synthesis of fused images is achieved through the utilization of semantic layouts generated via unsupervised learning. With the introduction of Attention Mechanism, the relationships between each pair of pixel points are gained to construct soft semantic layouts and further capture the global context information to make the same kind of semantics show the same fusion effect. By leveraging the semantic information, our method enables the automatic learning of fusion weights for two source images at the same spatial position. In comparison with other state-of-the-art image fusion methods, our experimental results obtained excellent performance both on qualitative results and quantitative indicators. Moreover, our method retains the high-level semantic information to the greatest extent, which is one of our outstanding characteristics. © 2024 SPIE. All rights reserved.

关键词： Image fusion

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Guided Filter in Least Squares to Remove Non-uniform Strong Noise of Underwater Target Image

Guided Filter in Least Squares to Remove Non-uniform Strong ...

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International Conference on Image, Vision and Intelligent Systems, ICIVIS 2021

作者： Liu, Guang Wu, Shikang Shi, Yu Hua, Xia School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology Wuhan430205 China

ISBN: (纸本)9789811669620

Underwater target detection will be interfered by underwater non-uniform strong noise (organic matter, suspended particles, etc.), in order to solve this problem, a new denoising method (DF-LS) is proposed based on the method of embedding bilateral filter (BLF-LS) in least square method to keep image edge smooth. Firstly, the guiding filter and the fast edge-preserving two-dimensional smoothing filter based on indicator function are introduced into the model to retain the edge of the underwater target and remove some small noise. At the same time, the guiding filter is embedded into the least square model to make the algorithm more efficient. Secondly, according to the non-uniform characteristics of noise, the multi-scale iteration of characteristic pyramid is adopted to decompose the noise of different sizes iteratively, and in the process of multi-scale decomposition, the noise of different scales is decomposed and removed step by step. Experimental results show that, compared with other classical denoising methods, the proposed algorithm can better remove the underwater non-uniform strong noise and retain the target information. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Iterative methods

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Semi-supervised PolSAR Image Change Detection using Similarity Matching

Semi-supervised PolSAR Image Change Detection using Similari...

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ISPRS Technical Commission I Midterm Symposium on Intelligent Sensing and Remote Sensing Application

作者： Wang, Lei Peng, Lingmu Hong, Hanyu Zhao, Shuwei Lv, Qiwen Gui, Rong Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology Hubei Wuhan430205 China School of Geosciences and Info-physics Central South University Changsha410083 China

The lack of precisely labeled data limits the development of supervised polarimetric synthetic aperture radar (PolSAR) image change detection. Therefore, semi-supervised deep learning methods have recently demonstrated their significant capability for PolSAR image change detection. Similarity Matching (SimMatch) improves the performance of semi-supervised learning tasks across different benchmark datasets and different settings. Introducing SimMatch into the field of PolSAR image change detection can improve the performance of semi-supervised PolSAR image change detection under limited labeled data conditions. Usually, semi-supervision solves the problem of insufficient labeled data by generating pseudo-labels. However, when the pseudo-label method is simply applied, the model will fit on the confident but wrong pseudo-labels, resulting in poor performance. SimMatch offers a solution by requiring the strongly augmented view to share the same semantic similarity (i.e. label prediction) and instance characteristics (i.e. similarity between instances) with a weak augmented view for more intrinsic feature matching. Besides, by using a labeled memory buffer, the two similarities can be isomorphically transformed with each other by introducing the aggregating and unfolding techniques. Therefore, the semantic and instance pseudo-labels can be mutually propagated, and then, the detection performance of the PolSAR image change detection is improved. Experimental results on real PolSAR datasets demonstrated that SimMatch is an effective semi-supervised PolSAR change detection method and its performance surpasses some well-known change detection methods. Compared to the fully-supervised algorithm CWNN, the semi-supervised SimMatch algorithm can improve accuracy by up to 14.4%. © Author(s) 2024.

关键词： Change detection

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