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Nonlinear optical response of niobium telluride and its application for demonstrating pulsed fiber lasers

Journal of Materiomics 2024年第2期10卷 355-365页

作者： Xinxin Shang Yule Zhang Tuo Li Huanian Zhang Xiaofeng Zou S.Wageh Ahmed A.Al-Ghamdi Han Zhang Shuhao Si Dengwang Li Shandong Province Key Laboratory of Medical Physics and Image Processing Technology Shandong Provincial Key Laboratory of Optics and Photonic DeviceSchool of Physics and ElectronicsShandong Normal UniversityJinan250014China Institute of Microscale Optoelectronics College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen518060China Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co. Ltd.JinanShandongChina School of Physics and Optoelectronic Engineering Shandong University of TechnologyZibo255049China Department of Physics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia

Niobium telluride(NbTe_(2)),a kind of few-layer two-dimensional(2D)transition metal dichalcogenides(TMDs)material,has been theoretically predicted with nonlinear absorption properties and excellent optical ***,we experimentally demonstrated an Er-doped fiber(EDF)laser based NbTe_(2)as saturable absorber(SA).Few-layer NbTe_(2)nanosheets were successfully prepared by adopting the commonly used liquid-phase exfoliation(LPE)*** nonlinear optical response of highly stable few-layer NbTe_(2)was investigated through an open-aperture Z-scan laser measurement,the nonlinear absorption coefficient was 2.45×10^(-11)m/*** Q-switched and mode-locked operation centered at 1559 nm were recorded based on NbTe_(2)*** pulse duration was varied from 4.88 ms to 1.75 ms,and the adjustable range of repetition frequency is changed from 44.01 kHz to 64.12 kHz in passively Q-switched ***,a constant repetition rate of 5.33 MHz and pulse width of 2.67 ps were observed in mode-locked *** experimental results fully reveal the nonlinear optical prop-erties of NbTe_(2)used in pulsed fiber lasers and broaden its ultrafast applications in the optics field.

关键词： Niobium telluride Saturable absorber Z-scan Mode-locked pulse Fiber laser

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Automated liver segmentation and steatosis grading using deep learning on B-mode ultrasound images

Automated liver segmentation and steatosis grading using dee...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Vianna, Pedro Kulbay, Merve Boustros, Pamela Calce, Sara-Ivana Larocque-Rigney, Cassandra Patry-Beaudoin, Laurent Luo, Yi Hui Chaudary, Muawiz Kadoury, Samuel Nguyen, Bich Montagnon, Emmanuel Belilovsky, Eugene Wolf, Guy Chassé, Michaël Tang, An Cloutier, Guy Laboratory of Biorheology and Medical Ultrasonics Crchum Canada École Polytechnique de Montréal Canada Chum Department of Pathology Canada Mila - Quebec Ai Institute Canada Concordia University Canada Université de Montréal Department of Computer Sciences and Operations Research Canada Canada Clinical Laboratory of Image Processing Crchum Canada Département de Radiologie Canada Université de Montréal Institute of Biomedical Engineering Canada

ISBN: (纸本)9798350346459

Early detection of nonalcoholic fatty liver disease (NAFLD) is crucial to avoid further complications. Ultrasound is often used for screening and monitoring of hepatic steatosis, however it is limited by the subjective interpretation of images. computer assisted diagnosis could aid radiologists to achieve objective grading, and artificial intelligence approaches have been tested across various medical applications. In this study, we evaluated the performance of a two-stage hepatic steatosis detection deep learning framework, with a first step of liver segmentation and a subsequent step of hepatic steatosis classification. We evaluated the models on internal and external datasets, aiming to understand the generalizability of the framework. In the external dataset, our segmentation model achieved a Dice score of 0.92 (95% CI: 0.78, 1.00), and our classification model achieved an area under the receiver operating characteristic curve of 0.84 (95% CI: 0.79, 0.89). Our findings highlight the potential benefits of applying artificial intelligence models in NAFLD assessment. © 2023 IEEE.

关键词： Classification (of information)

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Small Object Detection via Precise Region-Based Fully Convolutional Networks

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computers, Materials & Continua 2021年第11期69卷 1503-1517页

作者： Dengyong Zhang Jiawei Hu Feng Li Xiangling Ding Arun Kumar Sangaiah Victor SSheng Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan411004China School of Computing Science and Engineering Vellore Institute of Technology(VIT)Vellore632014India Department of Computer Science Texas Tech UniversityLubbock79409TXUSA

In the past several years,remarkable achievements have been made in the field of object *** performance is generally improving,the accuracy of small object detection remains low compared with that of large object *** addition,localization misalignment issues are common for small objects,as seen in GoogLeNets and residual networks(ResNets).To address this problem,we propose an improved region-based fully convolutional network(R-FCN).The presented technique improves detection accuracy and eliminates localization misalignment by replacing positionsensitive region of interest(PS-RoI)pooling with position-sensitive precise region of interest(PS-Pr-RoI)pooling,which avoids coordinate quantization and directly calculates two-order integrals for position-sensitive score maps,thus preventing a loss of spatial precision.A validation experiment was conducted in which the Microsoft common objects in context(MS COCO)training dataset was *** showed an accuracy improvement of 3.7%for object detection tasks and an increase of 6.0%for small objects.

关键词： Small object detection precise R-FCN PS-Pr-RoI pooling two-stage detector

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UrduAI: Writeprints for Urdu Authorship Identification

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ACM Transactions on Asian and Low-Resource Language Information processing 2022年第2期21卷 1–18页

作者： Sarwar, Raheem Hassan, Saeed-Ul Research Group in Computational Linguistics Research Institute of Information and Language Processing University of Wolverhampton Wulfruna St Midlands WolverhamptonWV1 1LY United Kingdom Department of Computer Science Information Technology University 346-B Ferozepur Road Punjab Lahore21210 Pakistan

The authorship identification task aims at identifying the original author of an anonymous text sample from a set of candidate authors. It has several application domains such as digital text forensics and information retrieval. These application domains are not limited to a specific language. However, most of the authorship identification studies are focused on English and limited attention has been paid to Urdu. However, existing Urdu authorship identification solutions drop accuracy as the number of training samples per candidate author reduces and when the number of candidate authors increases. Consequently, these solutions are inapplicable to real-world cases. Moreover, due to the unavailability of reliable POS taggers or sentence segmenters, all existing authorship identification studies on Urdu text are limited to the word n-grams features only. To overcome these limitations, we formulate a stylometric feature space, which is not limited to the word n-grams feature only. Based on this feature space, we use an authorship identification solution that transforms each text sample into a point set, retrieves candidate text samples, and relies on the nearest neighbors classifier to predict the original author of the anonymous text sample. To evaluate our solution, we create a significantly larger corpus than existing studies and conduct several experimental studies that show that our solution can overcome the limitations of existing studies and report an accuracy level of 94.03%, which is higher than all previous authorship identification works. © 2021 Association for Computing Machinery.

关键词： Text processing

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Provable Discriminative Hyperspherical Embedding for Out-of-Distribution Detection 39

Provable Discriminative Hyperspherical Embedding for Out-of-...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zou, Zhipeng Wan, Sheng Li, Guangyu Han, Bo Liu, Tongliang Zhao, Lin Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Hong Kong Baptist University China Sydney AI Centre The University of Sydney Sydney Australia Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)157735897X

Out-of-distribution (OOD) detection aims to identify the test examples that do not belong to the distribution of training data. The distance-based methods, which identify OOD examples based on their distances from the centroids of in-distribution (ID) examples, have demonstrated promising OOD detection performance. However, the objectives utilized in prior approaches are typically designed for classification and thus might not yield sufficient discriminative power to distinguish between ID and OOD examples. Therefore, this paper proposes a prototype-based contrastive learning framework for OOD detection, which is termed provable Discriminative Hyperspherical Embedding (DHE). The proposed framework provides a theoretical analysis of inter-class dispersion, which is proved to be fundamental in reducing the false positive rate (FPR) on OOD examples. Based on this, we devise an angular spread loss to achieve the maximal dispersion of the prototypes of different classes prior to training. Subsequently, a prototype-enhanced contrastive loss is introduced to align embeddings of ID examples closely with their corresponding prototypes. In our proposed DHE, the maximal prototype dispersion is theoretically proved, thereby avoiding the pitfalls of local optima commonly encountered by most existing methods. Experimental results demonstrate the effectiveness of our proposed DHE, which showcases a remarkable reduction in FPR95 (i.e., 5.37% on CIFAR-100) and more than doubling the computational efficiency when compared with the state-of-the-art methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Contrastive Learning

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Ordinal distribution regression for gait-based age estimation

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science China(Information sciences) 2020年第2期63卷 21-34页

作者： Haiping ZHU Yuheng ZHANG Guohao LI Junping ZHANG Hongming SHAN Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Department of Biomedical Engineering Rensselaer Polytechnic Institute

computer vision researchers prefer to estimate age from face images because facial features provide useful information. However, estimating age from face images becomes challenging when people are distant from the camera or occluded. A person’s gait is a unique biometric feature that can be perceived efficiently even at a distance. Thus, gait can be used to predict age when face images are not ***, existing gait-based classification or regression methods ignore the ordinal relationship of different ages, which is an important clue for age estimation. This paper proposes an ordinal distribution regression with a global and local convolutional neural network for gait-based age estimation. Specifically, we decompose gait-based age regression into a series of binary classifications to incorporate the ordinal age ***, an ordinal distribution loss is proposed to consider the inner relationships among these classifications by penalizing the distribution discrepancy between the estimated value and the ground truth. In addition,our neural network comprises a global and three local sub-networks, and thus, is capable of learning the global structure and local details from the head, body, and feet. Experimental results indicate that the proposed approach outperforms state-of-the-art gait-based age estimation methods on the OULP-Age dataset.

关键词： computer vision deep learning ordinal distribution regression global and local features gaitbased age estimation

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Simulated Data for SAR Tomographic Reconstruction in Urban Areas

Simulated Data for SAR Tomographic Reconstruction in Urban A...

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Earth Observation and Geo-Spatial Information (ICEOGI), International Conference on

作者： Ishak Daoud Saoussen Belhadj-Aissa Faiza Hocine Assia Kourgli Department of Telecommunication Image Processing and radiation Lab University of Science and Technology Houari Boumediene Algiers Algeria Jet Propulsion Laboratory California Institute of Technology Pasadena California USA

The evaluation of SAR tomographic reconstruction models requires an examination of their robustness with respect to various parameters. Typically, a simple simulation of reflectivity profiles with different scatters at different elevations and SNRs is used to evaluate the robustness of any reconstruction model. However, these simulation setups do not account for most of the geometric acquisition variables present in the reconstruction of real data. Most of the data used for SAR tomographic reconstruction in urban areas are acquired using high-resolution X-band sensors because of their weak penetration, which aids in recovering the geometry of the target. In this work, we propose simulating an urban area acquisition scene that considers the primary acquisition parameters of high-resolution X-band sensors. By doing so, one can simulate various measurements for different building shapes and elevations, providing a more comprehensive evaluation of the reconstruction methods. In this simulation, the geometry of SAR tomography is respected by considering different geometry distortions such as layover, foreshortening, and shadowing. The simulation is evaluated by implementing different reconstruction methods to the simulated data. Results obtained show that sparse reconstruction methods such as 11 and 12 norms and SL1MMER are more suitable to evaluate the reconstruction due to the high-resolution acquisitions. On the other hand, we used other conventional reconstruction models such as SVD-Weiner and MUSIC for assessment purposes.

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Evolution of AVS video coding standards: twenty years of innovation and development

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science China(Information sciences) 2022年第9期65卷 50-73页

作者： Siwei MA Li ZHANG Shiqi WANG Chuanmin JIA Shanshe WANG Tiejun HUANG Feng WU Wen GAO Institute of Digital Media School of Computer Science Peking University Bytedance Inc. Department of Computer Science City University of Hong Kong CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China

Ever since the founding of the Audio and Video Coding Standard(AVS) Workgroup of China in 2002, it has been dedicated to advancing and innovating the digital audio-video industry with highly efficient and economical encoding/decoding technologies. Three representative generations of video coding standards have been finalized and published, consistently improving the coding performance in the past two *** series of AVS standards establish solid foundations for ubiquitous video applications in the areas including acquisition, coding, production, delivery, integrated system, public service, general screen content, and mixed reality media. Along with the standardization process, an extensive amount of studies have been carried out on efficiency-aware designation, algorithm optimization, and hardware implementation of these innovative video coding techniques. This paper explains how those developed techniques provide a lasting impact on the video coding community, extensively, technologically, and systematically. In particular, we provide a comprehensive survey of the three generations of the standards, and timely and in-depth summarize the efforts of the AVS video coding standards in the twenty years. The rate-distortion performance comparisons,in particular in terms of the 8K ultra-high-definition(UHD) contents, reflect the elegant design of the state-of-the-art AVS3 standards. We have also elaborated on a variety of well-established and promising applications, including commercial level real-time 8K encoder, high-frame-rate decoder chip for cell phone,and live streaming solution for sports. In addition, the China Central Television(CCTV) of China Media Group(CMG), the state television of China, has officially launched the first 8K broadcasting channel(CCTV-8K) since 2021 using AVS3. Given the significant success realized by the AVS standards, it is envisioned that a new era of 8K UHD video is arriving.

关键词： video coding AVS standards video applications intelligent coding

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Swarming Behavior of Harris Hawks Optimizer for Arabic Opinion Mining

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computers, Materials & Continua 2021年第12期69卷 4129-4149页

作者： Diaa Salam Abd Elminaam Nabil Neggaz Ibrahim Abdulatief Ahmed Ahmed El Sawy Abouelyazed Department of Information Systems Faculty of Computers and Artificial IntelligenceBenha University12311Egypt Department of Computer Science Faculty of Computer ScienceMisr International UniversityEgypt Universite des Sciences at de la Technologie d’Oran Mohamed Boudiaf USTO-MBBP 1505EL M’naouer31000 OranLaboratoire Signal Image Parole(SIMPA)Department d’informatiqueFaculte des Mathematiques et InformatiqueAlgerie Department of Computer Science Faculty of Computers and Artificial IntelligenceBenha University12311Egypt Department of Computer Science Obour High Institute for Computers and InformaticsEgypt

At present,the immense development of social networks allows generating a significant amount of textual data,which has facilitated researchers to explore the field of opinion *** addition,the processing of textual opinions based on the term frequency-inverse document frequency method gives rise to a dimensionality *** study aims to detect the nature of opinions in the Arabic language employing a swarm intelligence(SI)-based algorithm,Harris hawks algorithm,to select the most relevant *** experimental study has been tested on two datasets:Arabic Jordanian General Tweets and Opinion Corpus for *** terms of accuracy and number of features,the results are better than those of other SI based algorithms,such as grey wolf optimizer and grasshopper optimization algorithm,and other algorithms in the literature,such as differential evolution,genetic algorithm,particle swarm optimization,basic and enhanced whale optimizer algorithm,slap swarm algorithm,and ant–lion optimizer.

关键词： Arabic opinion mining Harris hawks optimizer feature selection AJGT and OCA datasets

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Data-Driven Discovery of Stochastic Differential Equations

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Engineering 2022年第10期17卷 244-252页

作者： Yasen Wang Huazhen Fang Junyang Jin Guijun Ma Xin He Xing Dai Zuogong Yue Cheng Cheng Hai-Tao Zhang Donglin Pu Dongrui Wu Ye Yuan Jorge Gonçalves Jürgen Kurths Han Ding School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Mechanical Engineering University of KansasLawrenceKS 66045USA HUST-Wuxi Research Institute Wuxi 214174China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Department of Plant Sciences University of CambridgeCambridge CB23EAUK Luxembourg Centre for Systems Biomedicine University of LuxembourgBelvaux 4367Luxembourg Department of Physics Humboldt University of BerlinBerlin 12489Germany Department of Complexity Science Potsdam Institute for Climate Impact ResearchPotsdam 14473Germany

Stochastic differential equations(SDEs)are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different *** identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system’s *** practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data *** study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning(SBL)technique to search for a parsimonious,yet physically necessary representation from the space of candidate basis *** importantly,we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series *** effectiveness of the proposed framework is demonstrated using real data on stock and oil prices,bearing variation,and wind speed,as well as simulated data on well-known stochastic dynamical systems,including the generalized Wiener process and Langevin *** framework aims to assist specialists in extracting stochastic mathematical models from random phenomena in the natural sciences,economics,and engineering fields for analysis,prediction,and decision making.

关键词： Data-driven method System identification Sparse Bayesian learning Stochastic differential equations Random phenomena

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