检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Khan, Asifullah Sohail, Anabia Fiaz, Mustansar Hassan, Mehdi Afridi, Tariq Habib Marwat, Sibghat Ullah Munir, Farzeen Ali, Safdar Naseem, Hannan Zaheer, Muhammad Zaigham Ali, Kamran Sultana, Tangina Tanoli, Ziaurrehman Akhter, Naeem Pattern Recognition Lab DCIS PIEAS Nilore Islamabad45650 Pakistan PIEAS Nilore Islamabad45650 Pakistan Deep Learning Lab Center for Mathematical Sciences PIEAS Nilore Islamabad45650 Pakistan Center of Secure Cyber-Physical Security Systems Khalifa University Abu Dhabi United Arab Emirates IBM Research United States Department of Computer Science Air University Islamabad Pakistan Department of Computer Science and Engineering Kyung Hee University Global Campus 1732 Gyeonggi-do Yongin17104 Korea Republic of Department of Electrical Engineering and Automation Aalto University Finland Finnish Center of Artificial Center Finland Faculty of Engineering and Green Technology Universiti Tunku Abdul Rahman Malaysia Computer Vision Department Mohamed Bin Zayed University of Artificial Intelligence United Arab Emirates Karachi Pakistan Department of Electronics and Communication Engineering Hajee Mohammad Danesh Science and Technology University Bangladesh HiLIFE University of Helsinki Finland

Vision Transformers (ViTs) have recently demonstrated remarkable performance in computer vision tasks. However, their parameter-intensive nature and reliance on large amounts of data for effective performance have shifted the focus from traditional human-annotated labels to unsupervised learning and pretraining strategies that uncover hidden structures within the data. In response to this challenge, self-supervised learning (SSL) has emerged as a promising paradigm. SSL leverages inherent relationships within the data itself as a form of supervision, eliminating the need for manual labeling and offering a more scalable and resource-efficient alternative for model training. Given these advantages, it is imperative to explore the integration of SSL techniques with ViTs, particularly in scenarios with limited labeled data. Inspired by this evolving trend, this survey aims to systematically review SSL mechanisms tailored for ViTs. We propose a comprehensive taxonomy to classify SSL techniques based on their representations and pre-training tasks. Additionally, we discuss the motivations behind SSL, review prominent pre-training tasks, and highlight advancements and challenges in this field. Furthermore, we conduct a comparative analysis of various SSL methods designed for ViTs, evaluating their strengths, limitations, and applicability to different scenarios. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model

arXiv

引用

arXiv 2024年

作者： Fu, Ming-Xiang Song, Yu Lv, Jia-Meng Cao, Liang Jia, Peng Li, Nan Li, Xiang-Ru Liu, Ji-Feng Luo, A-Li Qiu, Bo Shen, Shi-Yin Tu, Liang-Ping Wang, Li-Li Wei, Shou-Lin Yang, Hai-Feng Yi, Zhen-Ping Zou, Zhi-Qiang National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan030024 China School of Astronomy and Space Science University of Chinese Academy of Sciences Beijing101408 China Key lab of Space Astronomy and Technology National Astronomical Observatories Beijing100101 China School of Computer Science South China Normal University Guangzhou510631 China CAS Key Laboratory of Optical Astronomy National Astronomical Observatories Beijing100101 China University of Chinese Academy of Sciences Nanjing211135 China University of Science and Technology Beijing Beijing100083 China Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China School of Computer and Information Dezhou University Dezhou253023 China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China School of Computer Science and Technology Taiyuan University of Science and Technology Taiyuan30024 China School of Mechanical Electrical and Information Engineering Shandong University Weihai264209 China Nanjing University of Posts & Telecommunications Nanjing210023 China School of Science University of Science and Technology LiaoNing Anshan114051 China

The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the Universe. However, effectively analyzing this vast amount of data poses a significant challenge. Astronomers are turning to deep learning techniques to address this, but the methods are limited by their specific training sets, leading to considerable duplicate workloads too. Hence, as an example to present how to overcome the issue, we built a framework for general analysis of galaxy images, based on a large vision model (LVM) plus downstream tasks (DST), including galaxy morphological classification, image restoration, object detection, parameter extraction, and more. Considering the low signal-to-noise ratio of galaxy images and the imbalanced distribution of galaxy categories, we have incorporated a Human-in-the-loop (HITL) module into our large vision model, which leverages human knowledge to enhance the reliability and interpretability of processing galaxy images interactively. The proposed framework exhibits notable few-shot learning capabilities and versatile adaptability to all the abovementioned tasks on galaxy images in the DESI legacy imaging surveys. Expressly, for object detection, trained by 1000 data points, our DST upon the LVM achieves an accuracy of 96.7%, while ResNet50 plus Mask R-CNN gives an accuracy of 93.1%;for morphology classification, to obtain AUC ∼ 0.9, LVM plus DST and HITL only requests 1/50 training sets compared to ResNet18. Expectedly, multimodal data can be integrated similarly, which opens up possibilities for conducting joint analyses with datasets spanning diverse domains in the era of multi-message astronomy. © 2024, CC BY.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

High-frequency oscillations in the atmosphere above a sunspot umbra

arXiv

引用

arXiv 2018年

作者： Wang, Feng Deng, Hui Bo, L.I. Feng, Song Xianyong, B.A.I. Deng, Linhua Yang, Yunfei Zhike, X.U.E. Wang, Rui School of Physics and Electronic Engineering Guangzhou University Guangzhou510006 China Yunnan Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Shandong Provincial Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment Institute of Space Sciences Shandong University Weihai264209 China CAS Key Laboratory of Solar Activity National Astronomical Observatories Beijing100012 China Yunnan Observatories Chinese Academy of Sciences Kunming650216 China

We use high spatial and temporal resolution observations, simultaneously obtained with the New Vacuum Solar Telescope and Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory, to investigate the high-frequency oscillations above a sunspot umbra. A novel time–frequency analysis method, namely the synchrosqueezing transform (SST), is employed to represent their power spectra and to reconstruct the high-frequency signals at different solar atmospheric layers. A validation study with synthetic signals demonstrates that SST is capable to resolving weak signals even when their strength is comparable with the high-frequency noise. The power spectra, obtained from both SST and the Fourier transform, of the entire umbral region indicate that there are significant enhancements between 10 and 14 mHz (labeled as 12 mHz) at different atmospheric layers. Analyzing the spectrum of a photospheric region far away from the umbra demonstrates that this 12 mHz component exists only inside the umbra. The animation based on the reconstructed 12 mHz component in AIA 171 Å illustrates that an intermittently propagating wave first emerges near the footpoints of coronal fan structures, and then propagates outward along the structures. A time–distance diagram, coupled with a subsonic wave speed (∼ 49 km s−1), highlights the fact that these coronal perturbations are best described as upwardly propagating magnetoacoustic slow waves. Thus, we first reveal the high-frequency oscillations with a period around one minute in imaging observations at different height above an umbra, and these oscillations seem to be related to the umbral perturbations in the photosphere. Copyright © 2018, The Authors. All rights reserved.

关键词： Magnetohydrodynamics

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Neuro-Fuzzy Control Approach for Robot's Trajectory Tracking

Design and Implementation of Neuro-Fuzzy Control Approach fo...

引用

International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Kiruba Sandou D Sunad kumara A N Binod Kumar Choudhary Shashikala Gurpur Sarishma Natrayan L M. SivaramKumar Department of Robotics and Automation Manakula Vinayagar Institute of Technology Pondicherry India Department of Computer Science and Engineering BGS Institute of Technology Adichunchanagiri University Mandya Karnataka India Department of Electrical and Electronics Engineering ARKA Jain University Jamshedpur Jharkhand India Faculty of Law Symbiosis Law School (SLS) Symbiosis International (Deemed University) (SIU) Pune Maharashtra India Department of Management Studies Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamilnadu India Department of EEE Karpagam Academy of higher education Coimbatore Tamiinadu

Achieving precise trajectory tracking while minimizing errors, reducing settling time, and curbing overshoot presents a significant challenge in the domain of robot-manipulator control. In response, this paper proposes a novel controller design for robot manipulators, incorporating two distinct approaches: a conventional fuzzy controller and an advanced Neuro-Fuzzy controller. These controllers are tailored to elevate trajectory tracking performance by simultaneously optimizing time characteristics in robot manipulator responses. To assess their efficacy, a range of test scenarios is devised, encompassing different trajectory types, including linear and nonlinear paths. Upon comparative analysis, the results highlight an intriguing contrast: while the fuzzy controller exhibits higher maximum overshoot and longer settling times in the robot's response, the Neuro-Fuzzy controller consistently demonstrates superior performance. The comprehensive error analysis such as Integral Square Error (ISE) and Integral Absolute Error (IAE) further underscores the capability of the Neuro-Fuzzy-based robot manipulator in delivering trajectory tracking precision. This study contributes to the advancement of trajectory control techniques for robot manipulators, paving the way for enhanced automation and performance across various applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Compact Source for Quasi-Periodic Pulsation in an M-class Solar Flare

arXiv

引用

arXiv 2019年

作者： Yuan, Ding Feng, Song Li, Dong Ning, ZhongJun Tan, Baolin Institute of Space Science and Applied Technology Harbin Institute of Technology Shenzhen Guangdong518055 China Key Laboratory of Solar Activity National Astronomical Observatories Chinese Academy of Sciences Beijing100012 China Yunnan Astronomical Observatory Chinese Academy of Sciences PO Box 110 Kunming650011 China Yunnan Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Key Laboratory for Dark Matter and Space Science Purple Mountain Observatory Chinese Academy of Sciences Nanjing210034 China

Quasi-periodic pulsations (QPP) are usually found in the light curves of solar and stellar flares, they carry the features of time characteristics and plasma emission of the flaring core, and could be used to diagnose the coronas of the Sun and remote stars. In this study, we combined the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory and the Nobeyama Radioheliograph (NoRH) to observe an M7.7 class flare occurred at active region 11520 on 19 July 2012. A QPP was detected both in the AIA 131 Å bandpass and the NoRH 17 GHz channel, it had a period of about four minutes. In the spatial distribution of Fourier power, we found that this QPP originated from a compact source and that it overlapped with the X-ray source above the loop top. The plasma emission intensities in the AIA 131 Å bandpass were highly correlated within this region. The source region is further segmented into stripes that oscillated with distinctive phases. Evidence in this event suggests that this QPP was likely to be generated by intermittent energy injection into the reconnection region. Copyright © 2019, The Authors. All rights reserved.

关键词： Magnetohydrodynamics

来源：评论

学校读者我要写书评

暂无评论

Preface

Advances in Intelligent Systems and Computing

引用

Advances in Intelligent Systems and Computing 2018年 620卷 v-vi页

作者： Omatu, Sigeru Rodríguez, Sara Villarrubia, Gabriel Faria, Pedro Sitek, Pawel Prieto, Javier Faculty of Engineering Department of Electronics Information and Communication Engineering Osaka Institute of Technology OsakaOsaka Japan Faculty of Science Department of Computer Science and Automation Control University of Salamanca Salamanca Spain GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Instituto Superior de Engenharia do Porto Porto Portugal Faculty of Electrical Engineering and Computer Science Department of Control and Management Systems Department of Information Systems Kielce University of Technology Kielce Poland

来源：评论

学校读者我要写书评

暂无评论

An Opponent Colour LGMD Neural Network for Collision Detection at Night with Thermal Camera

SSRN

引用

SSRN 2023年

作者： Zhang, Yicheng Han, Huizi Luan, Hao Hua, Mu Liu, Mei Cuayahuitl, Heriberto Yue, Shigang School of Automation Guangdong University of Petrochemical Technology 139 Guanduer Road Guangdong Maoming525000 China School of Computer Science University of Lincoln Brayford Pool LincolnLN6 7TS United Kingdom Faculty of Engineering The Hong Kong Polytechnic University 11 Yuk Choi Road 999077 Hong Kong School of Computer Science Tianjin University of Technology and Education No.1310 Dagu South Road Hexi District Tianjin300222 China School of Computing and Mathematical Sciences University of Leicester University Road LeicesterLE1 7RH United Kingdom

It is an enormous challenge for intelligent robots or vehicles to detect and avoid collisions at night because of poor light conditions. Thermal cameras capture the night scenes with temperature maps, often showing in different pseudo-colour modes to enhance the visual effects for the human eyes. Since the features of approaching objects could have been well enhanced in the pseudo colour outputs of a thermal camera, colour cues could likely help the collision detector - lobula giant movement detector (LGMD) to pick up the collision cues nicely. However, no investigation has been published on this aspect, and it is unclear whether the LGMD-like visual neural networks can take pseudo-colour information as inputs for collision detection in extremely dim conditions. In this study, we proposed a model consisting of three sub-networks, each dealing with one specific opponent colour channel, i.e., black-white, red-green, and yellow-blue. A collision alarm will be triggered if any channel’s output has exceeded its threshold for a few successive frames. Systematical experiments have been carried out to verify the proposed neural network with different thermal pseudo-colour modes in various nighttime scenarios. Our experiments demonstrated that the proposed bioinspired collision detection system works well in detecting colliding objects in direct collision courses at low light conditions quickly. The proposed method showed its potential to be part of the sensor systems for future robots or vehicles at night or in other extreme light conditions to avoid fatal collisions. © 2023, The Authors. All rights reserved.

关键词： Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Social Bot Detection via Structural Information Theory

arXiv

引用

arXiv 2024年

作者： Peng, Hao Zhang, Jingyun Huang, Xiang Hao, Zhifeng Li, Angsheng Yu, Zhengtao Yu, Philip S. School of Cyber Science and Technology Beihang University No. 37 Xue Yuan Road Haidian District Beijing100191 China State Key Laboratory of Public Big Data Guizhou University No. 2708 South Section of Huaxi Avenue Huaxi District Guizhou Province Guiyang City550025 China Guangxi Key Lab of Multi-source Information Mining & Security Guangxi Normal University Guilin541004 China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Kunming650500 China College of Science University of Shantou No. 243 University Road Shantou515063 China School of Computer Science and Engineering Beihang University No. 37 Xue Yuan Road Haidian District Beijing100191 China Faculty of Information Engineering and Automation Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Kunming650500 China Department of Computer Science University of Illinois at Chicago ChicagoIL60607 United States

Research on social bot detection plays a crucial role in maintaining the order and reliability of information dissemination while increasing trust in social interactions. The current mainstream social bot detection models rely on black-box neural network technology, e.g., Graph Neural Network, Transformer, etc., which lacks interpretability. In this work, we present UnDBot, a novel unsupervised, interpretable, yet effective and practical framework for detecting social bots. This framework is built upon structural information theory. We begin by designing three social relationship metrics that capture various aspects of social bot behaviors: Posting Type Distribution, Posting Influence, and Follow-to-follower Ratio. Three new relationships are utilized to construct a new, unified, and weighted social multi-relational graph, aiming to model the relevance of social user behaviors and discover long-distance correlations between users. Second, we introduce a novel method for optimizing heterogeneous structural entropy. This method involves the personalized aggregation of edge information from the social multi-relational graph to generate a two-dimensional encoding tree. The heterogeneous structural entropy facilitates decoding of the substantial structure of the social bots network and enables hierarchical clustering of social bots. Thirdly, a new community labeling method is presented to distinguish social bot communities by computing the user's stationary distribution, measuring user contributions to network structure, and counting the intensity of user aggregation within the community. Compared with ten representative social bot detection approaches, comprehensive experiments demonstrate the advantages of effectiveness and interpretability of UnDBot on four real social network datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Information theory

来源：评论

学校读者我要写书评

暂无评论

Cross-ethnicity face anti-spoofing recognition challenge: A review

arXiv

引用

arXiv 2020年

作者： Liu, Ajian Li, Xuan Wan, Jun Liang, Yanyan Escalera, Sergio Escalante, Hugo Jair Madadi, Meysam Jin, Yi Wu, Zhuoyuan Yu, Xiaogang Tan, Zichang Yuan, Qi Yang, Ruikun Zhou, Benjia Guo, Guodong Li, Stan Z. Faculty of Information Technology Avenida WaiLong Taipa Macau China School of Computer and Information Technology Beijing Jiaotong University Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Science Beijing China Universitat de Barcelona and Computer Vision Center Barcelona Instituto Nacional de Astrofísica Óptica y Electrónica Puebla Mexico School of Software Beihang University Beijing China Institute of Deep Learning Baidu Research and National Engineering Laboratory for Deep Learning Technology and Application Beijing Westlake University Hangzhou China

Face anti-spoofing is critical to prevent face recognition systems from a security breach. The biometrics community has achieved impressive progress recently due the excellent performance of deep neural networks and the availability of large datasets. Although ethnic bias has been verified to severely affect the performance of face recognition systems, it still remains an open research problem in face anti-spoofing. Recently, a multi-ethnic face anti-spoofing dataset, CASIA-SURF CeFA, has been released with the goal of measuring the ethnic bias. It is the largest up to date cross-ethnicity face anti-spoofing dataset covering 3 ethnicities, 3 modalities, 1;607 subjects, 2D plus 3D attack types, and the first dataset including explicit ethnic labels among the recently released datasets for face *** organized the Chalearn Face Anti-spoofing Attack Detection Challenge which consists of single-modal (e.g., RGB) and multi-modal (e.g., RGB, Depth, Infrared (IR)) tracks around this novel resource to boost research aiming to alleviate the ethnic bias. Both tracks have attracted 340 teams in the development stage, and finally 11 and 8 teams have submitted their codes in the single-modal and multi-modal face anti-spoofing recognition challenges, respectively. All the results were verified and re-ran by the organizing team, and the results were used for the final ranking. This paper presents an overview of the challenge, including its design, evaluation protocol and a summary of results. We analyze the top ranked solutions and draw conclusions derived from the competition. In addition we outline future work directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Large dataset

来源：评论

学校读者我要写书评

暂无评论

Joint Registration of Multiple Point Sets by Preserving Global and Local Structure

Joint Registration of Multiple Point Sets by Preserving Glob...

引用

International Conference on Information Fusion

作者： Hao Zhu Bin Guo Ka-Veng Yuen Henry Leung Yongfu Li Zhen Tian Department of Automation Chongqing University of Posts and Telecommunications Chongqing P. R. China Faculty of Science and Technology University of Macau Macao P. R. China Department of Electrical and Computer Engineering University of Calgary Calgary Alberta Canada

In previous work on joint multiple point sets registration, the multiple point sets are often formulated by a Gaussian mixture model (GMM) and the registration is then cast to a clustering problem, which aims to exploit global relationships on the multiple point sets. However, local relationships on the multiple point sets are ignored in the state-of-the-art joint multiple point sets registration techniques. In this paper, the multiple point sets are assumed to be generated from a GMM. Local features of the multiple point sets, such as shape context, are proposed to infer the membership probabilities of the GMM. The problem of joint multiple point sets registration can be performed by maximum likelihood of the GMM. The parameters of GMM and registration are estimated by an expectation maximization algorithm. Comprehensive experiments demonstrate that our proposed method has better performance than the state-of-the-art methods.

关键词： Multiple point sets registration Local features Gaussian mixture model Expectation maximization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：