检索结果-内蒙古大学图书馆

arXiv 2020年

作者： Yang, Jiaqi Huang, Zhiqiang Quan, Siwen Zhang, Qian Zhang, Yanning Cao, Zhiguo National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University China School of Software Northwestern Polytechnical University Xi’an710129 China School of Electronic and Control Engineering Chang’an University Xi’an710064 China School of Resources and Environment Hubei University Wuhan430062 China National Key Laboratory of Science and Technology on Multi-spectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

This paper focuses on developing efficient and robust evaluation metrics for RANSAC hypotheses to achieve accurate 3D rigid registration. Estimating six-degree-of-freedom (6-DoF) pose from feature correspondences remains a popular approach to 3D rigid registration, where random sample consensus (RANSAC) is a de-facto choice to this problem. However, existing metrics for RANSAC hypotheses are either time-consuming or sensitive to common nuisances, parameter variations, and different application scenarios, resulting in performance deterioration in overall registration accuracy and speed. We alleviate this problem by first analyzing the contributions of inliers and outliers, and then proposing several efficient and robust metrics with different designing motivations for RANSAC hypotheses. Comparative experiments on four standard datasets with different nuisances and application scenarios verify that the proposed metrics can significantly improve the registration performance and are more robust than several state-of-the-art competitors, making them good gifts to practical applications. This work also draws an interesting conclusion, i.e., not all inliers are equal while all outliers should be equal, which may shed new light on this research problem. Copyright © 2020, The Authors. All rights reserved.

关键词： Deterioration

来源：评论

学校读者我要写书评

暂无评论

Existence theorem of finite krasner hyperfields

arXiv

引用

arXiv 2021年

作者： Tsafack, Surdive Atamewoue Amassayoga, Ogadoa Onasanya, Babatunde O. Feng, Yuming School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Chongqing404100 China Department of Mathematics Higher Teacher Training College University of Yaounde 1 Cameroon Department of Mathematics Faculty of Science University of Yaounde 1 Cameroon Key Laboratory of Intelligent Information Processing and Control Chongqing Three China Gorges University Chongqing404100 China Department of Mathematics Uni-versity of Ibadan Nigeria School of Computer Science and Engineering Chongqing Three Gorges University China

关键词： Algebra

来源：评论

学校读者我要写书评

暂无评论

Protecting privacy of users in brain-computer interface applications

arXiv

引用

arXiv 2019年

作者： Agarwal, Anisha Dowsley, Rafael McKinney, Nicholas D. Wu, Dongrui Lin, Chin-Teng De Cock, Martine Nascimento, Anderson C.A. School of Engineering and Technology University of Washington TacomaWA98402 United States Department of Computer Science Bar-Ilan University Israel School of Engineering and Technology University of Washington TacomaWA98402 United States Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan China School of Software University of Technology Sydney Australia Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent9000 Belgium

Machine learning (ML) is revolutionizing research and industry. Many ML applications rely on the use of large amounts of personal data for training and inference. Among the most intimate exploited data sources is electroencephalogram (EEG) data, a kind of data that is so rich with information that application developers can easily gain knowledge beyond the professed scope from unprotected EEG signals, including passwords, ATM PINs, and other intimate data. The challenge we address is how to engage in meaningful ML with EEG data while protecting the privacy of users. Hence, we propose cryptographic protocols based on Secure Multiparty Computation (SMC) to perform linear regression over EEG signals from many users in a fully privacy-preserving (PP) fashion, i.e. such that each individual's EEG signals are not revealed to anyone else. To illustrate the potential of our secure framework, we show how it allows estimating the drowsiness of drivers from their EEG signals as would be possible in the unencrypted case, and at a very reasonable computational cost. Our solution is the first application of commodity-based SMC to EEG data, as well as the largest documented experiment of secret sharing based SMC in general, namely with 15 players involved in all the computations. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

On fuzzy alternate control systems

On fuzzy alternate control systems

引用

International Workshop on Advanced Computational intelligence (IWACI)

作者： Babatunde Oluwaseun Onasanya Yuming Feng Wei Zhang Shiping Wen Ning Tang Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou Chongqing China University of Ibadan Ibadan Nigeria Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Chongqing Three Gorges University Wanzhou Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Wanzhou Chongqing China Australian AI Institute Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China

Some researchers have worked on intermittent control and alternate control. In both cases, the choice of the control was a constant quantity. But, in real life, this situation is hard to come by for the reason that control may vary with time and circumstances owing to machine or human errors or both. Hence is the need to employ a method in which the control matrix is rather uncertain as is obtainable in real life. In this paper, we consider a more general model of both intermittent and alternate control which allows the control matrix to be fuzzy (uncertain). It turns out that both the classical intermittent and classical alternate controls are recovered in this mode.

关键词： Adaptation models Computational modeling control systems Computational intelligence

来源：评论

学校读者我要写书评

暂无评论

New results on anti-synchronization of switched neural networks with time-varying delays and lag signals

引用

Neural networks : the official journal of the International Neural Network Society 2016年 81卷 52-8页

作者： Yuting Cao Shiping Wen Michael Z Q Chen Tingwen Huang Zhigang Zeng School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: wenshiping226@***. The Department of Mechanical Engineering The University of Hong Kong Hong Kong. Texas A & M University at Qatar Doha 5825 Qatar.

This paper investigates the problem of global exponential anti-synchronization of a class of switched neural networks with time-varying delays and lag signals. Considering the packed circuits, the controller is dependent on the output of the system as the inner states are very hard to measure. Therefore, it is necessary to investigate the controller based on the output of the neuron cell. Through theoretical analysis, it is obvious that the obtained ones improve and generalize the results derived in the previous literature. To illustrate the effectiveness, a simulation example with applications in image encryptions is also presented in the paper.

关键词： Anti-synchronization Exponential stability Switched neural networks

来源：评论

学校读者我要写书评

暂无评论

Harmony-Search and Otsu based System for Coronavirus Disease (COVID-19) Detection using Lung CT Scan images

arXiv

引用

arXiv 2020年

作者： Rajinikanth, V. Dey, Nilanjan Raj, Alex Noel Joseph Hassanien, Aboul Ella Santosh, K.C. Raja, N. Sri Madhava Department of Electronics and Instrumentation Engineering St. Joseph’s College of Engineering Chennai600119 India Department of Information Technology Techno India College of Technology KolkataWest Bengal700156 India Key Laboratory of Digital Signal and Image Processing of Guangdong Province Department of Electronic Engineering College of Engineering Shantou University Shantou Guangdong China Faculty of Computers and Artificial Intelligence Cairo University Egypt Department of Computer Science University of South Dakota 414 E Clark St VermillionSD57069 United States

Pneumonia is one of the foremost lung diseases and untreated pneumonia will lead to serious threats for all age groups. The proposed work aims to extract and evaluate the Coronavirus disease (COVID-19) caused pneumonia infection in lung using CT scans. We propose an image-assisted system to extract COVID-19 infected sections from lung CT scans (coronal view). It includes following steps: (i) Threshold filter to extract the lung region by eliminating possible artifacts;(ii) image enhancement using Harmony-Search-Optimization and Otsu thresholding;(iii) image segmentation to extract infected region(s);and (iv) Region-of-interest (ROI) extraction (features) from binary image to compute level of severity. The features that are extracted from ROI are then employed to identify the pixel ratio between the lung and infection sections to identify infection level of severity. The primary objective of the tool is to assist the pulmonologist not only to detect but also to help plan treatment process. As a consequence, for mass screening processing, it will help prevent diagnostic burden. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

Cross-receptive Focused Inference Network for Lightweight image Super-Resolution

arXiv

引用

arXiv 2022年

作者： Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Zhou, Jiantao Yang, Jian Qi, Guo-Jun The Intelligent Visual Information Perception Laboratory Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210046 China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China The School of Communication and Information Engineering Shanghai University Shanghai200444 China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing210094 China The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China The State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science Faculty of Science and Technology University of Macau 999078 China The School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China The Research Center for Industries of the Future The School of Engineering Westlake University Hangzhou310024 China OPPO Research SeattleWA98101 United States

Recently, Transformer-based methods have shown impressive performance in single image super-resolution (SISR) tasks due to the ability of global feature extraction. However, the capabilities of Transformers that need to incorporate contextual information to extract features dynamically are neglected. To address this issue, we propose a lightweight Cross-receptive Focused Inference Network (CFIN) that consists of a cascade of CT Blocks mixed with CNN and Transformer. Specifically, in the CT block, we first propose a CNN-based Cross-Scale Information Aggregation Module (CIAM) to enable the model to better focus on potentially helpful information to improve the efficiency of the Transformer phase. Then, we design a novel Cross-receptive Field Guided Transformer (CFGT) to enable the selection of contextual information required for reconstruction by using a modulated convolutional kernel that understands the current semantic information and exploits the information interaction within different self-attention. Extensive experiments have shown that our proposed CFIN can effectively reconstruct images using contextual information, and it can strike a good balance between computational cost and model performance as an efficient model. Source codes will be available at https://***/IVIPLab/CFIN. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Dynamic Ca2+ sensitivity of BK channels

Dynamic Ca2+ sensitivity of BK channels

引用

The 4th International Ion Channel Conference(第四届国际离子通道会议)

作者： Panpan Hou Jianming Cui Ding Jiuping Feng Xiao Ming Yuchi Guohui Zhang Ying Wu Wei Wang Wenping Zeng Mingyue Ding Zhengxing Wu Department of pharmacology Soochow University college of pharmaceutical Sciences SuzhouChina Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Department of Biomedical Engineering College of Life Science and Technology Wuhan China Department of Biomedical Engineering Center for the Investigation of Membrane Excitability Disorders Cardiac Bioelectricity and Arrhythmia Center Washington University St Louis MOUSA Key Laboratory of Molecular Biophysics Huazhong University of Science and Technology Ministry of Education College of Life Science and Technology Wuhan China Department of Biomedical Engineering Center for the Investigation of Membrane Excitability Disorders Cardiac Bioelectricity and Arrhythmia Center Washington University St Louis MOUSA

来源：评论

学校读者我要写书评

暂无评论

有向动态网络的自发恢复（英文）

引用

Engineering 2024年第6期 208-214页

作者：刘雪明闫贤 H.Eugene Stanley School of Artificial Intelligence and Automation & The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems & the Key Laboratory of Image Processing Huazhong University of Science and Technology Center for Polymer Studies Department of Physics Boston University

Complex networked systems, which range from biological systems in the natural world to infrastructure systems in the human-made world, can exhibit spontaneous recovery after a failure; for example, a brain may spontaneously return to normal after a seizure, and traffic flow can become smooth again after a jam. Previous studies on the spontaneous recovery of dynamical networks have been limited to undirected networks. However, most real-world networks are directed. To fill this gap, we build a model in which nodes may alternately fail and recover, and we develop a theoretical tool to analyze the recovery properties of directed dynamical networks. We find that the tool can accurately predict the final fraction of active nodes, and the prediction accuracy decreases as the fraction of bidirectional links in the network increases, which emphasizes the importance of directionality in network dynamics. Due to different initial states, directed dynamical networks may show alternative stable states under the same control parameter, exhibiting hysteresis behavior. In addition, for networks with finite sizes, the fraction of active nodes may jump back and forth between high and low states, mimicking repetitive failure-recovery processes. These findings could help clarify the system recovery mechanism and enable better design of networked systems with high resilience.

关键词：

来源：评论

学校读者我要写书评

暂无评论

一种实用的二维工业CT重建算法

引用

中国体视学与图像分析 2005年第3期10卷 189-192页

作者：李慧田捷张兆田 Department of Education Technology Capital Normal University Beijing 100037 China Medical Image Processing Group Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences P. O. Box 2728 Beijing 100080 China Department of Information Science National Natural Science Foundation of China Beijing 100085 China

Computed tomography plays an important role in industrial non-destructive testing, medical applications, astronomy and many other fields to look inside the scanned object and to analysis its inner structures. A non-destructive testing software have been developed to efficiently detect inner flaws of space industrial components. As the core of our software, reconstruction algorithms including preprocess of raw data, re-arrange algorithm and filtered back-projection algorithms have been described in detail in this article. With real raw data from CASC of China, experimental results verified the applied reconstruction algorithm in our software. Furthermore, forward algorithms simulating generation of fan-beam raw data are also presented in this article.

关键词：二维工业CT 图象重建计算方法计算机系统

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：