检索结果-内蒙古大学图书馆

7th International Conference on Information, Communication and Networks, ICICN 2019

作者： Zhang, Yanping Xiao, Zhifeng Yang, Jianjun Wraith, Katerina Mosca, Patrick Department of Computer Science Gonzaga University SpokaneWA United States Department of Computer Science and Software Engineering Penn State Erie the Behrend College EriePA United States Department of Computer Science and Information Systems University of North Georgia GA United States Apple Inc. ClaytonCA United States

ISBN: (纸本)9781728104263

Smart supermarkets are a recent innovation that allows customers to have a seamless shopping experience. The Internet of Things (IoT) is a key component of smart supermarkets. Take AmazonGo as an example, it successfully implements cashier-less store checkout. However, many staff members are still required to support the running of the supermarket. Labor is always a big cost. In this paper, we propose a hybrid solution for smart supermarkets based on actuator networks as well as IoT, in order to save labor costs and to serve customers effectively and efficiently. © 2019 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Taming Self-Supervised Learning for Presentation Attack Detection: De-Folding and De-Mixing

arXiv

引用

arXiv 2021年

作者： Kong, Zhe Zhang, Wentian Liu, Feng Luo, Wenhan Liu, Haozhe Shen, Linlin Ramachandra, Raghavendra College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China School of Cyber Science and Technology Sun Yat-sen University Shenzhen Campus Guangdong Shenzhen518107 China Norwegian University of Science and Technology Gjøvik2818 Norway

Biometric systems are vulnerable to Presentation Attacks (PA) performed using various Presentation Attack Instruments (PAIs). Even though there are numerous Presentation Attack Detection (PAD) techniques based on both deep learning and hand-crafted features, the generalization of PAD for unknown PAI is still a challenging problem. In this work, we empirically prove that the initialization of the PAD model is a crucial factor for the generalization, which is rarely discussed in the community. Based on such observation, we proposed a self-supervised learning-based method, denoted as DF-DM. Specifically, DF-DM is based on a global-local view coupled with De-Folding and De-Mixing to derive the task-specific representation for PAD. During De-Folding, the proposed technique will learn region-specific features to represent samples in a local pattern by explicitly minimizing generative loss. While De-Mixing drives detectors to obtain the instance-specific features with global information for more comprehensive representation by minimizing interpolation-based consistency. Extensive experimental results show that the proposed method can achieve significant improvements in terms of both face and fingerprint PAD in more complicated and hybrid datasets when compared with state-of-the-art methods. When training in CASIA-FASD and Idiap Replay-Attack, the proposed method can achieve an 18.60% Equal Error Rate (EER) in OULU-NPU and MSU-MFSD, exceeding baseline performance by 9.54%. The source code of the proposed technique is available at https://***/kongzhecn/dfdm. Copyright © 2021, The Authors. All rights reserved.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Detect Stepping-stone Intrusion by Mining Network Traffic using k-Means Clustering

Detect Stepping-stone Intrusion by Mining Network Traffic us...

引用

IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： Lixin Wang Jianhua Yang Mary Mccormick Peng-Jun Wan Xiaohua Xu TSYS School of Computer Science Columbus State University GA USA Illinois Institute of Technology Chicago Illinois USA College of Computing and Software Engineering Kennesaw State University GA USA

ISBN: (数字)9781728198293

ISBN: (纸本)9781728198309

Attackers on the Internet often launch network intrusions through compromised hosts, called stepping-stones, in order to reduce the chance of being detected. In a stepping-stone attack, an attacker uses a chain of hosts on the Internet as relay machines and remotely login these hosts using tools such as SSH. An effective method to detect stepping-stone intrusion is to estimate the length of a connection chain. In this paper, we develop an efficient algorithm to detect stepping-stone intrusion by mining network traffic using the k-Means clustering algorithm. Our proposed detection algorithm does not require a large number of TCP packets to be captured and processed. The length of a connection chain can be accurately determined by using our proposed detection method. Our proposed detection algorithm is more efficient and easier to implement than all of the existing connection-chain based approaches for stepping-stone intrusion detection. The effectiveness and correctness of our proposed detection algorithm are verified through well-designed network experiments.

关键词： Clustering algorithms Telecommunication traffic Tools Internet Detection algorithms Relays Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Joystick Mapping in Virtual Reality Shooting Game 3

Joystick Mapping in Virtual Reality Shooting Game

引用

3rd International Conference on Innovative Computing, ICIC 2019

作者： Nabeel, Muhammad Ahmad, Faiq Din, Hooria Muslih Ud Ahsan, Muhammad Ali, Usman Asif, Arslan University of Management and Technology Software Engineering Department Lahore Pakistan University of Management and Technology Computer Science Department Lahore Pakistan UCD Energy Institute University College Dublin Dublin Ireland

ISBN: (纸本)9781728146829

A method to use for mapping VR-Box joystick with shooting game input controls that include key mapping of every joystick key from the joystick with the game itself. Key mapping was observed and then the source code keys we're mapped with the joystick keys. The joystick holds major 4 buttons with a 360-degree moveable joystick with 2 supporting keys making them total of 6 keys. In this paper we will discuss mapping of Google Virtual Reality plugin with First Person Shooting plugin. The integration of joystick with VR-Box helped the gameplay even more controllable. The joystick keys are responsible for invoking key features of game as it can be connected via Bluetooth with the mobile headset to ensure long range wireless connectivity. The device converts the keys triggered from joystick to enable the features inside the game. © 2019 IEEE.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

K-B2S+: A one-dimensional CNN model for AF detection with short single-lead ECG waves from wearable devices

引用

Digital Communications and Networks 2024年

作者： Bo Fang Zhaocheng Yu Li-bo Zhang Yue Teng Junxin Chen School of Computer Science University of Sydney NSW 2008 Australia College of Medicine and Biological Information Engineering Northeastern University Shenyang 110004 China Department of Radiology General Hospital of the Northern Theater of the Chinese People's Liberation Army Shenyang 110004 China School of Software Dalian University of Technology Dalian 116621 China

Wearable signal analysis is an important technology for monitoring physiological signals without interfering with an individual's daily behavior. As detecting cardiovascular diseases can dramatically reduce mortality, arrhythmia recognition using ECG signals has attracted much attention. In this paper, we propose a single-channel convolutional neural network to detect Atrial Fibrillation (AF) based on ECG signals collected by wearable devices. It contains 3 primary modules. All recordings are firstly uniformly sized, normalized, and Butterworth low-pass filtered for noise removal. Then the preprocessed ECG signals are fed into convolutional layers for feature extraction. In the classification module, the preprocessed signals are fed into convolutional layers containing large kernels for feature extraction, and the fully connected layer provides probabilities. During the training process, the output of the previous pooling layer is concatenated with the vectors of the convolutional layer as a new feature map to reduce feature loss. Numerous comparison and ablation experiments are performed on the 2017 PhysioNet/CinC Challenge dataset, demonstrating the superiority of the proposed method.

关键词： Single-lead ECG Wearable devices Feature concatenating Atrial fibrillation

来源：评论

学校读者我要写书评

暂无评论

Differentiable refraction-tracing for mesh reconstruction of transparent objects

arXiv

引用

arXiv 2020年

作者： Lyu, Jiahui Wu, Bojian Lischinski, Dani Cohen-Or, Daniel Huang, Hui Shenzhen University China Alibaba Group China Hebrew University of Jerusalem Israel Shenzhen University Tel Aviv University Israel College of Computer Science & Software Engineering Shenzhen University China

Capturing the 3D geometry of transparent objects is a challenging task, ill-suited for general-purpose scanning and reconstruction techniques, since these cannot handle specular light transport phenomena. Existing state-of-the-art methods, designed specifically for this task, either involve a complex setup to reconstruct complete refractive ray paths, or leverage a data-driven approach based on synthetic training data. In either case, the reconstructed 3D models suffer from over-smoothing and loss of fine detail. This paper introduces a novel, high precision, 3D acquisition and reconstruction method for solid transparent objects. Using a static background with a coded pattern, we establish a mapping between the camera view rays and locations on the background. Differentiable tracing of refractive ray paths is then used to directly optimize a 3D mesh approximation of the object, while simultaneously ensuring silhouette consistency and smoothness. Extensive experiments and comparisons demonstrate the superior accuracy of our method. Copyright © 2020, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

来源：评论

学校读者我要写书评

暂无评论

Diabetic Retinopathy Grade and Macular Edema Risk Classification Using Convolutional Neural Networks

Diabetic Retinopathy Grade and Macular Edema Risk Classifica...

引用

2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019

作者： He, Jia Shen, Linlin Ai, Xingfang Li, Xuechen College of Computer Science and Software Engineering Shenzhen University Shenzhen Guangdong province China Research and Development Center Konka Group Co. Ltd. Shenzhen Guangdong province China

ISBN: (纸本)9781728137209

Diabetic retinopathy (DR) is one of the major causes of blindness in the western world. Effective treatment of DR is available, when detected early enough, which makes this a vital process. computers are able to obtain much quicker classifications once trained, giving the ability to aid clinicians in real-time classification. This work employed a deep convolutional neural network (CNN) based method for diabetic retinopathy classification. Three independent CNNs were employed for the classification of DR grade, macular edema risk and multi-label, which included the combination of both grade and risk classes. A fusion method was used to combine all features extracted by the CNNs and make the final classification result. The classification accuracy of the grade and risk were 0.65 and 0.72, respectively. The classification results showed the proposed network fusion method can improve the performances on both task - DR grading and macular edema risk. © 2019 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Multi-scale feature fusion for breast tumor grading using dual-adaptive attention mechanisms

引用

Pattern Recognition 2026年 169卷

作者： Israr Hussain Zhihui Lai Heng Kong Fazil Hussain College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen 518060 China Department of Thyroid and Breast Surgery BaoAn Central Hospital of Shenzhen Shenzhen 518102 China Department of Medicine Provincial Head Quarter (PHQ) Hospital Gilgit 15711 Pakistan

Breast cancer is the most common malignant tumor in women worldwide. Early detection and timely treatment are crucial for improving survival rates and ensuring effective treatment planning. While existing methods primarily focus on classifying benign versus malignant tumors, accurate tumor grading remains underexplored. The scarcity of high-quality annotated datasets for advanced tumor grades, combined with their inherent similarity, limits model robustness and precise grading. To address these challenges, we propose a novel framework for breast tumor grading diagnosis that leverages multi-scale feature fusion with dual-adaptive attention mechanisms. This framework enhances grading performance by capturing both local and global information. It integrates information across multiple scales, improves feature representation, and enables the detection of subtle differences between grades. The framework consists of three primary modules: deep hybrid feature extraction, multi-scale feature fusion, and dual-adaptive attention mechanisms. Together, these modules enhance feature representation, capture salient information, and highlight discriminative features, ultimately improving grading accuracy. In addition, we constructed two distinct image datasets consisting of 17,058 ultrasound images and 1571 MRI images for breast tumor grading. Experimental results demonstrated the effectiveness of our framework, achieving a test accuracy of 0.89, a macro-average F1-score of 0.82, and a micro-average precision of 0.93, outperforming existing state-of-the-art methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Location Privacy Protection Scheme Based on Location Services 2019

Location Privacy Protection Scheme Based on Location Service...

引用

Proceedings of the 2019 the 9th International Conference on Communication and Network Security

作者： Chen Yang Wei Yan School of Software Dalian University of Foreign Languages Dalian China School of Computer Science and Technology Harbin Engineering University Harbin China Department of Information Liaoning Police College Dalian China School of Software Dalian University of Technology Dalian China

ISBN: (纸本)9781450376624

Location-based services (LBS) in the mobile internet applications are very important and provide a great convenience. However, at the same time it brings the threat of privacy leak. For location services, a location privacy protection scheme is proposed, which includes location hiding algorithm and query privacy protection algorithm. Q-Tree storage ensures that anonymous location units are as dispersed as possible. The point of interest (POI) with higher query probability is selected as the query content of anonymous location unit, which protects the user's query privacy. At the same time, private information retrieval technology (PIR) is used to provide users with higher privacy and security protection. Finally, the effectiveness of the scheme is proved by privacy analysis and experimental results.

关键词： K-anonymity Privacy Protection Location Service Q-Tree PIR

来源：评论

学校读者我要写书评

暂无评论

Structural combinatorial of network information system of systems based on evolutionary optimization method

arXiv

引用

arXiv 2020年

作者： Zhang, Tingting Lan, Yushi Song, Aiguo Liu, Kun Wang, Nan Computer and military software engineering PLA Army Engineering University Nanjing China National defense key laboratory China Electronics Technology Group Corporation Nanjing China College of Instrument Science and Engineering Southeast University Nanjing China College of Command and Control Engineering PLA Army Engineering University Nanjing China

The network information system is a military information network system with evolution characteristics. Evolution is a process of replacement between disorder and order, chaos and equilibrium. Given that the concept of evolution originates from biological systems, in this article, the evolution of network information architecture is analyzed by genetic algorithms, and the network information architecture is represented by chromosomes. Besides, the genetic algorithm is also applied to find the optimal chromosome in the architecture space. The evolutionary simulation is used to predict the optimal scheme of the network information architecture and provide a reference for system construction. Copyright © 2020, The Authors. All rights reserved.

关键词： Genetic algorithms

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：