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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Chen, Jiansong Zuo, Shikai Lin, Yun Tang, Kai Zou, Jianhang Feng, Naixing Cai, Yijun Xiamen University of Technology Smart Sensing Integrated Circuit Engineering Research Center of Universities in Fujian Province Xiamen361024 China Xiamen Wish Information Technology Co. Ltd Xiamen361006 China Anhui University Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Hefei China

ISBN: (纸本)9781665452366

Garbage classification is an essential work in daily life. With the development of artificial intelligence (AI), we have begun to use object detection to achieve garbage classification. However, the stacking and occlusion of garbage often make the detection performance unsatisfactory. In this paper, YOLOv5 algorithm is used for garbage detection and classification. YOLOv5 has three detection heads, which can detect objects at multiple scales. At the same time, Mosaic and Coarse Dropout image augmentation techniques are used to process our private data set of garbage, which improves the diversity of images. In this way, the target classification accuracy of the detection model can reach 75.7%, which is significantly improved compared with 69.9% without data augmentation. This paper provides a new technical support for the scene classification of stacked garbage based on deep learning. © 2022 IEEE.

关键词： Classification (of information)

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A Fractional-Order Logarithmic Adaptive Filtering Algorithm Under $\alpha$-Stable Noise

A Fractional-Order Logarithmic Adaptive Filtering Algorithm ...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Dazhi Sun Canping Yu Li Li Yingsong Li Wudang Xiao Yong Chen Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Aircraft Airworthiness Institute China Academy of Civil Aviation Science and Technology (Center of Aviation Safety Technology CAST) Beijing China

In practical applications, noise is more appropriately modelled as an a-stable random process than as a Gaussian process. To cope with a-stable noise, a fractional-order stochastic gradient descent (SGD) method is invented to adaptive filtering (AF) algorithms. When both input signal and noise follow α-stable random processes, the AF algorithms based on mean square error (MSE) criteria can be affected. Nevertheless, the fractional-order AF (FoAF) algorithm can effectively address this issue. For the purpose of better stability performance of the FoAF algorithm, different cost functions (CFs) are introduced into fractional-order SGD method. Based on the fractional-order derivative of a logarithmic CF (LCF), a fractional-order logarithmic adaptive filtering (FoLAF) algorithm is formed in this condition. Trials show that the FoLAF algorithm achieves faster convergence, excellent steady-state performance and superior tracking performance.

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MSCA-UNet: Multi-Scale Channel Adaptive Sensing Module for Medical Image Segmentation

MSCA-UNet: Multi-Scale Channel Adaptive Sensing Module for M...

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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Liangjin Diao Longfeng Shen Jiacong Chen Fangzhen Ge Mengwen Li Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior (ICACB) College of Computer Science and Technology Huaibei Normal University Huaibei Anhui China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei Anhui China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

Recent advancements in CNNs for medical image segmentation have focused on the combination of CNN and Transformer architectures to capture both local and global features. However, challenges remain, such as effectively utilizing fused features at the encoder-decoder bottleneck and addressing blurred object edges in datasets. To tackle these issues, we introduce a multi-scale channel adaptive sensing module, enhancing the model's representational and perceptual capabilities by integrating multi-scale and channel-specific information. Additionally, we propose a cross-perception module and multi-scale segmentation head to improve global coordination and multi-scale information gathering. Experiments on the ACDC and Synapse datasets demonstrate our model's superiority.

关键词： Image segmentation Adaptation models Head Image edge detection Computer architecture Transformers Market research Sensors Synapses Biomedical imaging

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Representation Purification for End-to-End Speech Translation

arXiv

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arXiv 2024年

作者： Zhang, Chengwei Zhou, Yue Zhao, Rui Chen, Yidong Shi, Xiaodong School of Informatics Xiamen University China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University Xiamen China

Speech-to-text translation (ST) is a cross-modal task that involves converting spoken language into text in a different language. Previous research primarily focused on enhancing speech translation by facilitating knowledge transfer from machine translation, exploring various methods to bridge the gap between speech and text modalities. Despite substantial progress made, factors in speech that are not relevant to translation content, such as timbre and rhythm, often limit the efficiency of knowledge transfer. In this paper, we conceptualize speech representation as a combination of content-agnostic and content-relevant factors. We examine the impact of content-agnostic factors on translation performance through preliminary experiments and observe a significant performance deterioration when content-agnostic perturbations are introduced to speech signals. To address this issue, we propose a Speech Representation Purification with Supervision Enhancement (SRPSE) framework, which excludes the content-agnostic components within speech representations to mitigate their negative impact on ST. Experiments on MuST-C and CoVoST-2 datasets demonstrate that SRPSE significantly improves translation performance across all translation directions in three settings and achieves preeminent performance under a transcript-free setting. Copyright © 2024, The Authors. All rights reserved.

关键词： Speech enhancement

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A Cell Condition-Sensitive Frequency Segmentation Method Based on the Sub-Band Instantaneous Energy Spectrum of Aluminum Electrolysis Cell Voltage

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Engineering 2021年第9期7卷 1282-1292页

作者： Zhaohui Zeng Weihua Gui Xiaofang Chen Yongfang Xie Hongliang Zhang Yubo Sun School of Automation Central South UniversityChangsha 410083China Key Laboratory of Intelligent Computing&Information Processing Ministry of EducationXiangtan UniversityXiangtan 411105China School of Metallurgy and Environment Central South UniversityChangsha 410083China

Cell voltage is a widely used signal that can be measured online from an industrial aluminum electrolysis cell.A variety of parameters for the analysis and control of industrial cells are calculated using the cell *** this paper,the frequency segmentation of cell voltage is used as the basis for designing filters to obtain these *** on the qualitative analysis of the cell voltage,the sub-band instantaneous energy spectrum(SIEP)is first proposed,which is then used to quantitatively represent the characteristics of the designated frequency bands of the cell voltage under various cell ***,a cell condition-sensitive frequency segmentation method is *** proposed frequency segmentation method divides the effective frequency band into the[0,0.001]Hz band of lowfrequency signals and the[0.001,0.050]Hz band of low-frequency noise,and subdivides the lowfrequency noise into the[0.001,0.010]Hz band of metal pad abnormal rolling and the[0.01,0.05]Hz band of sub-low-frequency *** with the instantaneous energy spectrum based on empirical mode decomposition,the SIEP more finely represents the law of energy change with time in any designated frequency band within the effective frequency band of the cell *** proposed frequency segmentation method is more sensitive to cell condition changes and can obtain more elaborate details of online cell condition information,thus providing a more reliable and accurate online basis for cell condition monitoring and control decisions.

关键词： Sub-band instantaneous energy spectrum Cell condition-sensitive frequency band Frequency segmentation Metal pad abnormal rolling Aluminum electrolysis

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Variable projection algorithms with sparse constraint for separable nonlinear models

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Control Theory and Technology 2024年第1期22卷 135-146页

作者： Hui-Lang Xu Guang-Yong Chen Si-Qing Cheng Min Gan Jing Chen College of Computer and Data Science Fuzhou UniversityFuzhou350116FujianChina Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhou350116FujianChina Key Laboratory of Intelligent Metro of Universities in Fujian Fuzhou UniversityFuzhou350116FujianChina Engineering Research Center of Big Data Intelligence Ministry of EducationFuzhou UniversityFuzhou350116FujianChina School of Science Jiangnan UniversityWuxi214122JiangsuChina

Separable nonlinear models are widely used in various fields such as time series analysis, system modeling, and machine learning, due to their flexible structures and ability to capture nonlinear behavior of data. However, identifying the parameters of these models is challenging, especially when sparse models with better interpretability are desired by practitioners. Previous theoretical and practical studies have shown that variable projection (VP) is an efficient method for identifying separable nonlinear models, but these are based on $L_2$ penalty of model parameters, which cannot be directly extended to deal with sparse constraint. Based on the exploration of the structural characteristics of separable models, this paper proposes gradient-based and trust-region-based variable projection algorithms, which mainly solve two key problems: how to eliminate linear parameters under sparse constraint;and how to deal with the coupling relationship between linear and nonlinear parameters in the model. Finally, numerical experiments on synthetic data and real time series data are conducted to verify the effectiveness of the proposed algorithms.

关键词： Variable projection(VP) Non-smooth constraint Separable nonlinear models

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Spatio-Temporal Coherent Snapshot Compressed Imaging with Time-Varying Composite Phase Masks

SSRN

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SSRN 2023年

作者： Zhang, Ru Zhang, Cheng Zhang, Liru Chen, Mingsheng Cheng, Hong Shen, Chuan Zhang, Quanbin Wei, Sui Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Province Hefei230601 China Advanced Laser Technology Laboratory of Anhui Province National University of Defense Technology Anhui Province Hefei230037 China

Snapshot compressed imaging (SCI) can encode an image sequence into a single-frame measurement and has the advantages of low requirements for physical sensors, low bandwidth/ memory requirements, and a fast acquisition speed. However, existing snapshot compressed imaging mainly focuses on incoherent imaging, such as video/hyperspectral imaging, and research on coherent imaging is rare. In this paper, snapshot compressed sensing is introduced for coherent imaging conditions, and a spatio-temporal coherent snapshot compressed imaging method with time-varying composite phase masks is proposed. Numerical experiments demonstrate the effectiveness and superiority of our proposed spatio-temporal coherent snapshot compressed imaging with time-varying composite phase masks method (CSCI-CPM) in terms of the reconstruction quality and robustness for both self-sparse and complex cases. © 2023, The Authors. All rights reserved.

关键词： Numerical methods

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Colors display with spatial light modulator based on inf-wavelength metal grating

Colors display with spatial light modulator based on inf-wav...

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2020 Applied Optics and Photonics China: Optoelectronics and Nanophotonics;and Quantum Information Technology, AOPC 2020

作者： Tao, Bo Wang, GuiZhu Wei, Sui Shen, Chuan Xu, ZhangMing Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Hefei230601 China

ISBN: (纸本)9781510639492

A spatial light modulator based on inf-wavelength gold grating structure, named GLCoS by us, has been devised and tested to meet the challenge of the high space-bandwidth product in holographic video display. A sample GLCoS has been made and its display color appears green. However, if it is to be a device of a display system, its color characteristics must be further investigated, that is, its ability to display RGB color and its color purity. There are two MIM (Metal-Insulator-Metal) in the GLCoS, inf-wavelength gold grating plus liquid crystal cell and aluminum electrode forms a hybridized MIM and inf-wavelength gold grating itself is a MIM acting as an open-end TM-FP (TM-Fabry-Pérot) resonator. Based on our previous study involving GLCoS theoretical model, simulation software platform (FDTD plus CST Studio Suite) and an experimentally verified sample of single color, we seek an engineering way with simplicity and compatibility in the sense of the technique to investigate the red-green-blue (RGB) color display with GLCoS. Among the huge parameter space including the geometry and size of the structure, material, wavelength and light incident angle. We choose to change width of the slit, incident angle, LC (liquid crystal) birefringence to find the appropriate GLCoS spectral characteristics. The simulation results show that the dynamic modulation of the RGB phase can be achieved in the visible light band, and its amount of phase modulation is close to 2π and high chromatographic purity. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Light modulators

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Investigation on a quantum algorithm for linear differential equations

arXiv

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arXiv 2024年

作者： Dong, Xiaojing Peng, Yizhe Tang, Qili Yang, Yin Yu, Yue Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education National Center for Applied Mathematics in Hunan School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

Ref. [BCOW17] introduced a pioneering quantum approach (coined BCOW algorithm) for solving linear differential equations with optimal error tolerance. Originally designed for a specific class of diagonalizable linear differential equations, the algorithm was extended by Krovi in [Kro23] to encompass broader classes, including non-diagonalizable and even singular matrices. Despite the common misconception, the original algorithm is indeed applicable to non-diagonalizable matrices, with diagonalisation primarily serving for theoretical analyses to establish bounds on condition number and solution error. By leveraging basic estimates from [Kro23], we derive bounds comparable to those outlined in the Krovi algorithm, thereby reinstating the advantages of the BCOW approach. Furthermore, we extend the BCOW algorithm to address time-dependent linear differential equations by transforming non-autonomous systems into higher-dimensional autonomous ones, a technique also applicable for the Krovi algorithm. © 2024, CC BY-NC-ND.

关键词： Consensus algorithm

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Lifetime Prediction of Topcon Modules Based on Accelerated Damp Heat Life Tests

SSRN

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SSRN 2025年

作者： Ren, Xingang Duan, Junwei Yang, Lixia Xu, Tao Yu, Yuanjie Chen, Zhiliang Lv, Ruirui Ye, Feihong Wang, Gang Ahmed, Rida Jiang, Hao Yang, Lixia Huang, Zhixiang Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei230601 China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei230601 China CSI Cells Co. Ltd. Suzhou215129 China Anhui University of Chinese Medicine China Hong Kong Polytechnic University Hong Kong

Tunnel Oxide Passivation Contacts (TOPCon) solar cells have achieved high efficiency and become mainstream product in the global photovoltaic (PV) market. However, their long-term reliability, especially under high-temperature and high-humidity conditions, lacks sufficient field validation, and there is a lack of lifetime prediction models for TOPCon modules. To address this, we developed a robust accelerated aging model by integrating an improved Peck model with a sigmoidal degradation function, incorporating internal humidity and temperature as critical factors. The model employs a particle swarm optimization (PSO) algorithm to calibrate activation energy and humidity sensitivity parameters, enabling precise degradation trajectory simulation. Validated through a "fitting + testing" framework, the model achieves high accuracy (RMSE = 0.7%) in predicting power degradation under Damp Heat (DH), Highly Accelerated Stress Test (HAST), and modified Pressure Cooker Test (mPCT) conditions. Accelerated aging tests reveal that DH-induced degradation primarily reduces fill factor (FF) due to finger corrosion, with minimal impact on Voc and Isc. Experimental validation using a non-commercial corrosion-sensitive BOM combination shows that polyolefin elastomer (POE)-encapsulated modules exhibit superior corrosion resistance, projecting a service lifetime 23 years longer than EVA/EVA encapsulation in high-humidity regions like Hainan. This work bridges the gap in TOPCon module lifetime prediction under extreme environments, offering actionable insights for optimizing encapsulation materials and enhancing reliability. The model provides a scalable framework for evaluating module performance under site-specific climatic conditions, accelerating the development of durable PV technologies. © 2025, The Authors. All rights reserved.

关键词： Corrosion resistance

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