检索结果-内蒙古大学图书馆

On Approximate Opacity of Stochastic Control Systems

IEEE Transactions on Automatic Control 2024年第6期70卷 3846-3861页

作者： Liu, Siyuan Yin, Xiang Dimarogonas, Dimos V. Zamani, Majid Kth Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Shanghai Jiao Tong University and Key Lab of System Control & Information Processing Ministry of Education Department of Automation Shanghai China University of Colorado Boulder Computer Science Department CO80309 United States Ludwig Maximilian University of Munich Computer Science Department Germany

This paper investigates an important class of information-flow security property called opacity for stochastic control systems. Opacity captures whether a system's secret behavior (a subset of the system's behavior that is considered to be critical) can be kept from outside observers. Existing works on opacity for control systems only provide a binary characterization of the system's security level by determining whether the system is opaque or not. In this work, we introduce a quantifiable measure of opacity that considers the likelihood of satisfying opacity for stochastic control systems modeled as general Markov decision processes (gMDPs). We also propose verification methods tailored to the new notions of opacity for finite gMDPs by using value iteration techniques. Then, a new notion called approximate opacity-preserving stochastic simulation relation is proposed, which captures the distance between two systems' behaviors in terms of preserving opacity. Based on this new system relation, we show that one can verify opacity for stochastic control systems using their abstractions (modeled as finite gMDPs). We also discuss how to construct such abstractions for a class of gMDPs under certain stability conditions. © 1963-2012 IEEE.

关键词： Stochastic control systems

来源：评论

学校读者我要写书评

暂无评论

Detecting Fake Political News on Social Media by Support Vector Machine Compared to Naive Bayes 2

Detecting Fake Political News on Social Media by Support Vec...

引用

2nd International Conference Computational and Characterization Techniques in Engineering and sciences, IC3TES 2024

作者： Sireesha, M. Tamilselvan, S. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Cloud Computing and Image Processing Tamil Nadu Chennai India

ISBN: (纸本)9798350364699

The primary objective is to enhance the precision of the Support Vector Machine and evaluate it in comparison to the Naive Bayes algorithm in terms of its ability to forecast fake political news on social media networks. This research work focuses on two groups: Support Vector Machine and Naive Bayes Algorithm, where each group is executed for 10 times. The ClinCalc software was used in calculating samples in which the alpha value is considered as 0.05, and the confidence interval of 95%. Result: There is a statistically significant difference between the algorithm used by Improved Support Vector Machine and Naive Baye with P value as 0.001 (Independent Sample t-Test P © 2024 IEEE.

关键词： Cloud Computing Innovative Fake News Detection Internet Access Naive Bayes Support Vector Machine

来源：评论

学校读者我要写书评

暂无评论

Anomaly Based Camera Prioritization in Large Scale Surveillance Networks

引用

computers, Materials & Continua 2022年第2期70卷 2171-2190页

作者： Altaf Hussain Khan Muhammad Hayat Ullah Amin Ullah Ali Shariq Imran Mi Young Lee Seungmin Rho Muhammad Sajjad Department of Software Sejong University143-747SeoulKorea Digital Image Processing Lab Islamia College Peshawar25000Pakistan Color Lab Department of Computer ScienceNorwegian University of Science and Technology(NTNU)2815GjovikNorway CORIS Institute Oregon State University97331OregonUSA

Digital surveillance systems are ubiquitous and continuously generate massive amounts of data,and manual monitoring is required in order to recognise human activities in public *** surveillance systems that can automatically identify normal and abnormal activities are highly desirable,as these would allow for efficient monitoring by selecting only those camera feeds in which abnormal activities are *** paper proposes an energy-efficient camera prioritisation framework that intelligently adjusts the priority of cameras in a vast surveillance network using feedback from the activity recognition *** proposed system addresses the limitations of existing manual monitoring surveillance systems using a three-step *** the first step,the salient frames are selected from the online video stream using a frame differencing method.A lightweight 3D convolutional neural network(3DCNN)architecture is applied to extract spatio-temporal features from the salient frames in the second ***,the probabilities predicted by the 3DCNN network and the metadata of the cameras are processed using a linear threshold gate sigmoid mechanism to control the priority of the *** proposed system performs well compared to state-of-theart violent activity recognition methods in terms of efficient camera prioritisation in large-scale surveillance *** experiments and an evaluation of activity recognition and camera prioritisation showed that our approach achieved an accuracy of 98%with an F1-score of 0.97 on the Hockey Fight dataset,and an accuracy of 99%with an F1-score of 0.98 on the Violent Crowd dataset.

关键词： Camera prioritisation surveillance networks convolutional neural network computer vision deep learning resource-constrained device violent activity recognition

来源：评论

学校读者我要写书评

暂无评论

Study of Some TMCs Heterostructures Band Diagrams for Photonics Applications 10

Study of Some TMCs Heterostructures Band Diagrams for Photon...

引用

10th International Conference on Information Technology and Nanotechnology, ITNT 2024

作者： Rymzhina, Anastasiia Andreev, Ivan Temirbulatov, Azamat Sharma, Prachi Platonov, Vladimir Pavelyev, Vladimir Mishra, Prabhash Tripathi, Nishant Samara National Research University Samara Russia Tamil Nadu Vellore India Image Processing Systems Institute Nrc 'Kurchatov Institute' Samara Russia Department Of Applied Science & Humanities New Delhi India

ISBN: (纸本)9798350372939

This paper presents the study results on the transition metal chalcogenides (TMCs) optoelectronic properties for photonics applications. To do this, titanium trisulfide TiS3 and titanium disulfide TiS2 were synthesized while molybdenum disulfide MoS2 and tungsten disulfide WS2 were exfoliated. Their band gaps were determined in order to calculate the band diagrams of the TiS3-MoS2, TiS2-TiS3, TiS2-WS2, MoS2-WS2, and compounds. The calculation results demonstrate the relevance of using different materials heterostructures for the development of new generation photodetectors. © 2024 IEEE.

关键词： Titanium compounds

来源：评论

学校读者我要写书评

暂无评论

Dynamic Frame Interpolation in Wavelet Domain

引用

IEEE Transactions on image processing 2023年 32卷 5296-5309页

作者： Kong, Lingtong Jiang, Boyuan Luo, Donghao Chu, Wenqing Tai, Ying Wang, Chengjie Yang, Jie Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Department of Automation Shanghai200240 China Tencent Youtu Laboratory Shanghai200233 China Nanjing University School of Intelligence Science and Technology Suzhou215163 China

Video frame interpolation is an important low-level vision task, which can increase frame rate for more fluent visual experience. Existing methods have achieved great success by employing advanced motion models and synthesis networks. However, the spatial redundancy when synthesizing the target frame has not been fully explored, that can result in lots of inefficient computation. On the other hand, the computation compression degree in frame interpolation is highly dependent on both texture distribution and scene motion, which demands to understand the spatial-temporal information of each input frame pair for a better compression degree selection. In this work, we propose a novel two-stage frame interpolation framework termed WaveletVFI to address above problems. It first estimates intermediate optical flow with a lightweight motion perception network, and then a wavelet synthesis network uses flow aligned context features to predict multi-scale wavelet coefficients with sparse convolution for efficient target frame reconstruction, where the sparse valid masks that control computation in each scale are determined by a crucial threshold ratio. Instead of setting a fixed value like previous methods, we find that embedding a classifier in the motion perception network to learn a dynamic threshold for each sample can achieve more computation reduction with almost no loss of accuracy. On the common high resolution and animation frame interpolation benchmarks, proposed WaveletVFI can reduce computation up to 40% while maintaining similar accuracy, making it perform more efficiently against other state-of-the-arts. © 1992-2012 IEEE.

关键词： Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

Single-Shot VR 23

Single-Shot VR

引用

Special Interest Group on computer Graphics and Interactive Techniques Conference - Emerging Technologies, SIGGRAPH 2023

作者： Qin, Yingsi Chen, Wei-Yu O'Toole, Matthew Sankaranarayanan, Aswin C. Image Science Lab at ECE Department Carnegie Mellon University United States Robotics Institute & Computer Science Department Carnegie Mellon University United States

ISBN: (纸本)9798400701542

The physical world has contents at varying depths, allowing our eye to squish or relax to focus at different distances;this is commonly referred to as the accommodation cue for human eyes. To allow a realistic 3D viewing experience, it is crucial to support the accommodation cue - the 3D display needs to show contents at different depths. However, supporting the native focusing of the eye has been an immense challenge to 3D displays. Commercial near-eye VR displays, which use binocular disparity as the primary cue for inducing depth perception, fail this challenge since all contents they show arise from a fixed depth - ignoring the focusing of the eye. Many research prototypes of VR displays do account for the accommodation cue;however, supporting accommodation cues invariably comes with performance loss among other typically assessed criteria for 3D displays. To tackle these challenges, we present a novel kind of near-eye 3D display that can create 3D scenes supporting realistic accommodation cues in a single shot, i.e., without using time multiplexing or eye tracking. This display, which we present in our demo, can stream 3D content over a large depth range, at 4K spatial resolution, and in real-time. Our display offers an exciting step forward towards a truly immersive real-time 3D experience. Participants will get to enjoy 3D movies and play interactive games in their demo experience. © 2023 Owner/Author.

关键词： Three dimensional displays

来源：评论

学校读者我要写书评

暂无评论

PCRTAM-Net:A Novel Pre-Activated Convolution Residual and Triple Attention Mechanism Network for Retinal Vessel Segmentation

引用

Journal of computer science & Technology 2023年第3期38卷 567-581页

作者：汪华登李紫正保罗黎兵兵潘细朋刘振丙蓝如师罗笑南 Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin 541004China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin 541004China School of Artificial Intelligence Guilin University of Electronic TechnologyGuilin 541004China Department of Pathology Ganzhou Municipal HospitalGanzhou 341000China

Retinal images play an essential role in the early diagnosis of ophthalmic *** segmentation of retinal vessels in color fundus images is challenging due to the morphological differences between the retinal vessels and the low-contrast *** the same time,automated models struggle to capture representative and discriminative retinal vascular *** fully utilize the structural information of the retinal blood vessels,we propose a novel deep learning network called Pre-Activated Convolution Residual and Triple Attention Mechanism Network(PCRTAM-Net).PCRTAM-Net uses the pre-activated dropout convolution residual method to improve the feature learning ability of the *** addition,the residual atrous convolution spatial pyramid is integrated into both ends of the network encoder to extract multiscale information and improve blood vessel information flow.A triple attention mechanism is proposed to extract the structural information between vessel contexts and to learn long-range feature *** evaluate the proposed PCRTAM-Net on four publicly available datasets,DRIVE,CHASE_DB1,STARE,and *** model achieves state-of-the-art performance of 97.10%,97.70%,97.68%,and 97.14%for ACC and 83.05%,82.26%,84.64%,and 81.16%for F1,respectively.

关键词： retinal image segmentation triple attention mechanism atrous convolution residual network

来源：评论

学校读者我要写书评

暂无评论

Training Deep Neural Classifiers with Soft Diamond Regularizers

Training Deep Neural Classifiers with Soft Diamond Regulariz...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Olaoluwa Adigun Bart Kosko Department of Electrical and Computer Engineering Signal and Image Processing Institute Los Angeles California

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

We introduce new soft diamond regularizers that both improve synaptic sparsity and maintain classification accuracy in deep neural networks. These parametrized regularizers outperform the state-of-the-art hard-diamond Laplacian regularizer of Lasso regression and classification. They use thick-tailed symmetric alpha-stable $(\mathcal{S}\alpha \mathcal{S})$ bell-curve synaptic weight priors that are not Gaussian and so have thicker tails. The geometry of the diamond-shaped constraint set varies from a circle to a star depending on the tail thickness and dispersion of the prior probability density function. Training directly with these priors is computationally intensive because almost all $\mathcal{S}\alpha \mathcal{S}$ probability densities lack a closed form. A precomputed lookup table removed this computational bottleneck. We tested the new soft diamond regularizers with deep neural classifiers on the three datasets CIFAR-10, CIFAR-100, and Caltech-256. The regularizers improved the accuracy of the classifiers. The improvements included 4.57% on CIFAR-10, 4.27% on CIFAR-100, and 6.69% on Caltech-256. They also outperformed $L_{2}$ regularizers on all the test cases. Soft diamond regularizers also outperformed $L_{1}$ lasso or Laplace regularizers because they better increased sparsity while improving classification accuracy. Soft-diamond priors substantially improved accuracy on CIFAR-10 when combined with dropout, batch, or data-augmentation regularization.

关键词： Training Accuracy Sparse approximation Stars Tail Machine learning Probability density function Diamond Table lookup Residual neural networks

来源：评论

学校读者我要写书评

暂无评论

Age Detection based on Facial Features Using Support Vector Machine

Age Detection based on Facial Features Using Support Vector ...

引用

2022 IEEE International Conference on Knowledge Engineering and Communication Systems, ICKES 2022

作者： Hiremath, Jayaprada S. Hiremath, Shantala S. Kumar, Sujith Hebbare, Elukoti Patil, Shantakumar B. Hiremath, Mrutyunjaya S. Research Scholar at Vtu Computer Science and Engineering Belgaum India Tata Elxsi Limited Specialist in Image Processing Bangalore India Bangalore India EMath Technology Pvt. Ltd. Department of Image Processing Bangalore India Sai Vidya Institute of Technology Computer Science and Engineering Bengaluru India

ISBN: (纸本)9781665456371

Face aging has been studied for decades. Determining age from a facial shot is key to our technique for diagnosing abnormal behavior. Security monitoring, forensics, biometrics, and Human-computer Interface (HCI) use facial age estimates. We only look at adults 1-75 in the UTK Face database, which covers 0 to 116 years. The database contains 23,708 face photos with age, gender, and ethnicity annotations. In work, preprocessing, feature extraction, feature selection, and age categorization are involved. Preprocessing adjusts images. computer vision uses Local Binary Pattern (LBP) and Histogram of Oriented Gradient (HOG) as visual descriptors, whereas fscmrmr is utilized for classification. Support Vector Machines (SVM) improve classification accuracy in highdimensional areas. The chosen characteristics are concatenated and passed to a multiclass SVM classifier to classify the images with 95.69% success. © 2022 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Model Based Anomaly Detection in High Dimensional DATA 6

Model Based Anomaly Detection in High Dimensional DATA

引用

6th International Conference on Advanced Technologies for Signal and image processing, ATSIP 2022

作者： Gatfaoui, Imen Solaiman, Basel Farah, Imed Riadh National Institute of Computer Science Riadi Laboratory Imt Atlantique Iti Laboratory Tunis Tunisia Imt Atlantique Department of Image and Information Processing Brest France National Institute of Computer Science Riadi Laboratory Tunis Tunisia

ISBN: (纸本)9781665451161

Anomaly detection is a growing research issue in several application domains. This paper attempts to provide a structured overview of anomaly detection research. A state-of-the-art of anomaly detection techniques is then presented. A classification of methods based both on the type of datasets (Big DATA, data flow, graphs, time series, etc.), application domains (fraud detection, intrusion detection, medical anomaly detection, etc.) and the approach considered (Deep Learning, statistical, classification, clustering based, etc.) is proposed. We propose a multi-vision approach of case base representation for anomaly detection in a high- dimensional data using Case-Based Reasoning. © 2022 IEEE.

关键词： Anomaly detection

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：