检索结果-内蒙古大学图书馆

Fusion of speech and handwritten signatures biometrics for person identification

International Journal of Speech Technology 2023年第4期26卷 833-850页

作者： Abushariah, Ahmad A. M. Abushariah, Mohammad A. M. Gunawan, Teddy Surya Chebil, J. Alqudah, Assal A. M. Ting, Hua-Nong Mustafa, Mumtaz Begum Peer Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Department of Computer Information Systems King Abdullah II School of Information Technology The University of Jordan Amman Jordan ECE Department Faculty of Engineering International Islamic University Malaysia Kuala Lumpur53100 Malaysia Department of Computer Science Faculty of Science and Information Technology Al-Zaytoonah University of Jordan Amman Jordan Department of Biomedical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

Automatic person identification (API) using human biometrics is essential and highly demanded compared to traditional API methods, where a person is automatically identified using his/her distinct characteristics including speech, fingerprint, iris, handwritten signatures, and others. The fusion of more than one human biometric produces bimodal and multimodal API systems that normally outperform single modality systems. This paper presents our work towards fusing speech and handwritten signatures for developing a bimodal API system, where fusion was conducted at the decision level due to the differences in the type and format of the features extracted. A data set is created that contains recordings of usernames and handwritten signatures of 100 persons (50 males and 50 females), where each person recorded his/her username 30 times and provided his/her handwritten signature 30 times. Consequently, a total of 3000 utterances and 3000 handwritten signatures were collected. The speech API used Mel-Frequency Cepstral Coefficients (MFCC) technique for features extraction and Vector Quantization (VQ) for features training and classification. On the other hand, the handwritten signatures API used global features for reflecting the structure of the hand signature image such as image area, pure height, pure width and signature height and the Multi-Layer Perceptron (MLP) architecture of Artificial Neural Network for features training and classification. Once the best matches for both the speech and the handwritten signatures API are produced, the fusion process takes place at decision level. It computes the difference between the two best matches for each modality and selects the modality of the maximum difference. Based on our experimental results, the bimodal API obtained an average recognition rate of 96.40%, whereas the speech API and the handwritten signatures API obtained average recognition rates of 92.60% and 75.20%, respectively. Therefore, the bimodal API system is a

关键词： Biometrics

来源：评论

学校读者我要写书评

暂无评论

Optimally Scheduling Single-Arm Multicluster Tools for Manufacturing Hybrid-Type Wafers

Optimally Scheduling Single-Arm Multicluster Tools for Manuf...

引用

2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Wang, Genghong Zhu, Qinghua Hou, Yan Qiao, Yan Wu, Naiqi Zhou, Mengchu School of Computer Science and Technology Guangdong University of Technology Guangzhou China Institute of Systems Engineering Macau University of Science and Technology Macau China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07920 United States

ISBN: (纸本)9798350337020

In semiconductor manufacturing, multicluster tools are widely employed for many wafer fabrication processes. With the demand for high-mix integrated circuit chips and shrinkage of circuit width, a scheme in which multiple wafer types are fabricated inside multicluster tools is adopted by wafer foundries to make more profits. Multiple wafer types, multiple robots, and wafer residency time constraints make the resulting scheduling problems challenging. This work focuses on scheduling a single-arm multicluster tool to process two wafer types concurrently subject to wafer residency time constraints in which a conventional one-wafer cycle and backward strategy are not efficient. With such properties, several necessary and sufficient conditions are presented to check the feasibility of a periodic schedule. Polynomial-time-complex algorithms are proposed to examine a tool's schedulability and coordinate multiple robots to handle wafers for schedulable scenarios. The cycle time of an obtained schedule can reach the lower bound. A practical example is used to show the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： hybrid-type wafers multicluster tools scheduling semiconductor manufacturing wafer fabrication

来源：评论

学校读者我要写书评

暂无评论

Blockchain Assisted Intrusion Detection System Using Differential Flower Pollination Model

引用

computers, Materials & Continua 2022年第12期73卷 4695-4711页

作者： Mohammed Altaf Ahmed Sara A Althubiti Dronamraju Nageswara Rao ELaxmi Lydia Woong Cho Gyanendra Prasad Joshi Sung Won Kim Department of Computer Engineering College of Computer Engineering&SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science and Engineering Chitkara University Institute of Engineering and TechnologyChitkara UniversityPunjab140401India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Software Convergence Daegu Catholic UniversityGyeongsan38430Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

Cyberattacks are developing gradually sophisticated,requiring effective intrusion detection systems(IDSs)for monitoring computer resources and creating reports on anomalous or suspicious *** the popularity of Internet of Things(IoT)technology,the security of IoT networks is developing a vital *** of the huge number and varied kinds of IoT devices,it can be challenging task for protecting the IoT framework utilizing a typical *** typical IDSs have their restrictions once executed to IoT networks because of resource constraints and ***,this paper presents a new Blockchain Assisted Intrusion Detection System using Differential Flower Pollination with Deep Learning(BAIDS-DFPDL)model in IoT *** presented BAIDS-DFPDLmodelmainly focuses on the identification and classification of intrusions in the IoT *** accomplish this,the presented BAIDS-DFPDL model follows blockchain(BC)technology for effective and secure data transmission among the ***,the presented BAIDSDFPDLmodel designs Differential Flower Pollination based feature selection(DFPFS)technique to elect ***,sailfish optimization(SFO)with Restricted Boltzmann Machine(RBM)model is applied for effectual recognition of *** simulation results on benchmark dataset exhibit the enhanced performance of the BAIDS-DFPDL model over other models on the recognition of intrusions.

关键词： Internet of things feature selection intrusion detection blockchain security deep learning

来源：评论

学校读者我要写书评

暂无评论

Content based Image Retrieval using K-Nearest Neighbours and Convolutional Neural Networks 15

Content based Image Retrieval using K-Nearest Neighbours and...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Kumar, C. Siva Bhaskaru, O. Komatlapalli, Bhargavi Areddula, Phani Sai Kumar Maddali, Manikanta Reddy, Busa Rajasekhar Tirupati India Dept. of CSE Gates Institute of Technology Gooty A.P Ananthapur India Department of Computer Science and Systems Engineering Sree Vidyanikethan Engineering College Tirupati India

ISBN: (纸本)9798331300579

Today, there is a lot of digital image material on the Internet. As the need for better image search tools grows, new waysmust be found to solve the problem of telling the difference betweenquestion pictures and received images. This study presents a new technique to enhance the searching of images in retrieval based on image content. The technique involves using several deep neural network methods, such as ResNet50, InceptionResNetV2,VGG19, InceptionV3, DenseNet121, Xception, and Improved CNN. These models make it easier to find interesting photos. The study tested thetechnique on the Dataset and a dataset from a Kaggle competition, using metrics like the confusion matrices, F1 scores, and mAP to assess the model performance. The tests show that the proposed system works very well, taking away some of the problems that come with picture searches being unclear and showing how well it can find appropriate images. © Grenze Scientific Society, 2024.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Noisy Node Classification by Bi-level Optimization Based Multi-Teacher Distillation 39

Noisy Node Classification by Bi-level Optimization Based Mul...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Liu, Yujing Wu, Zongqian Lu, Zhengyu Nie, Ci Wen, Guoqiu Zhu, Yonghua Zhu, Xiaofeng School of Computer Science and Engineering Guangxi Normal University Guilin China Guangxi Key Lab of Multisource Information Mining and Security Guangxi Normal University Guilin China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Information Engineering Anyang Institute of Technology Anyang China Information Systems Technology Design Pillar Singapore University of Technology and Design Singapore

ISBN: (纸本)157735897X

Previous graph neural networks (GNNs) usually assume that the graph data is with clean labels for representation learning, but it is not true in real applications. In this paper, we propose a new multi-teacher distillation method based on bi-level optimization (namely BO-NNC), to conduct noisy node classification on the graph data. Specifically, we first employ multiple self-supervised learning methods to train diverse teacher models, and then aggregate their predictions through a teacher weight matrix. Furthermore, we design a new bi-level optimization strategy to dynamically adjust the teacher weight matrix based on the training progress of the student model. Finally, we design a label improvement module to improve the label quality. Extensive experimental results on real datasets show that our method achieves the best results compared to state-of-the-art methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). 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

TizenRT OS Based Data Compression Algorithms for IoT Devices 4

TizenRT OS Based Data Compression Algorithms for IoT Devices

引用

4th IEEE International Conference on Computing, Communication, and Intelligent systems, ICCCIS 2023

作者： Chamak, Tanmoy Roy Kaushik, Sachi Singhal, Shiven Dadheech, Aditya Anitha, Prof. A. Jenicka, Prof. S. Thapa, Vidisha School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Samsung Research Institute Karnataka Bangalore India

ISBN: (纸本)9798350306118

The paper investigates the integration and adaptation of the LZ4 compression algorithm within the context of TizenRT, in addition to existing algorithms Miniz and LZMA. TizenRT, a real-Time operating system tailored for Internet of Things (IoT) devices, presents unique challenges in balancing compression efficiency and resource constraints. The study evaluates the performance of LZ4 alongside Miniz and LZMA in terms of compression ratios, processing overhead, and memory utilization. Experimental results demonstrate the feasibility of LZ4's adoption in TizenRT, highlighting its potential to enhance data compression and decompression operations while adhering to the stringent requirements of IoT devices. The findings contribute to the optimization of data management strategies within the TizenRT ecosystem. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Locating What You Need: Towards Adapting Diffusion Models to OOD Concepts In-the-Wild 38

Locating What You Need: Towards Adapting Diffusion Models to...

引用

38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Yang, Jianan Gao, Chenchao Xiao, Zhiqing Zhao, Junbo Wu, Sai Chen, Gang Wang, Haobo College of Computer Science and Technology Zhejiang University China Institute of Blockchain and Data Security China School of Software Technology Zhejiang University China International School of Information Science and Engineering Dalian University of Technology China

The recent large-scale text-to-image generative models have attained unprecedented performance, while people established adaptor modules like LoRA and DreamBooth to extend this performance to even more unseen concept tokens. However, we empirically find that this workflow often fails to accurately depict the out-of-distribution concepts. This failure is highly related to the low quality of training data. To resolve this, we present a framework called Controllable Adaptor Towards Out-of-Distribution Concepts (CATOD). Our framework follows the active learning paradigm which includes high-quality data accumulation and adaptor training, enabling a finer-grained enhancement of generative results. The aesthetics score and concept-matching score are two major factors that impact the quality of synthetic results. One key component of CATOD is the weighted scoring system that automatically balances between these two scores and we also offer comprehensive theoretical analysis for this point. Then, it determines how to select data and schedule the adaptor training based on this scoring system. The extensive results show that CATOD significantly outperforms the prior approaches with an 11.10 boost on the CLIP score and a 33.08% decrease on the CMMD metric. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

CASKA-CRT: Chinese Remainder Theorem Empowered Certificateless Aggregate Signcryption Scheme with Key Agreement in IoVs

IEEE Transactions on Intelligent Vehicles

引用

IEEE Transactions on Intelligent Vehicles 2024年第11期9卷 1-16页

作者： Hou, Yingzhe Cao, Yue Xiong, Hu Sun, Zhili Mumtaz, Shahid Tian, Daxin School of Cyber Science and Engineering Wuhan University Wuhan China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Institute of Communication Systems University of Surrey Guildford U.K Department of Applied Informatics Silesian University of Technology Akademicka Gliwice Poland State Key Laboratory of Vehicle-Infrastructure Integrated ITS the State Key Laboratory of Intelligent Transportation System and the School of Transportation Science and Engineering Beihang University Beijing China

To enhance the privacy of messages in Internet of Vehicles (IoVs), it is critical to preserve the communication security between Road Side Unit (RSU) and numerous vehicles. The primitive of signcryption is introduced to guarantee the confidentiality, integrity and unforgeability of transmitted messages. Nevertheless, the existing signcryption schemes fail to achieve a balance between security and efficiency. In this paper, we construct a Chinese remainder theorem (CRT) empowered certificateless aggregate signcryption scheme with key agreement (CASKA-CRT). As the vehicle joins and leaves dynamically, the proposed scheme can ensure the dynamic security via one modulo division operation. Besides, the certificateless aggregate signcryption and key agreement mechanisms are embedded. The former idea can both address the certificate management and key escrow problems, while the latter technology can create authentication as a premise of secure communication. Based on this construction, the hash-to-group operation and bilinear pairing are avoided, to realize a faster verification with the increased number of messages. Moreover, the security of proposed scheme is proved under the random oracle model. Finally, the performance analysis demonstrates the advantage of CASKA-CRT in terms of security and reliability over related works. IEEE

关键词： Public key cryptography

来源：评论

学校读者我要写书评

暂无评论

Motion path planning method based on map reference points

引用

Multimedia Tools and Applications 2024年 1-21页

作者： Yu, Wenbin Fan, Cheng Zhang, Chengjun Chen, Yadang Li, Yangsong Zhang, Yifan Yin, Na Cen, Xiaolin School of Software Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China School of Computer Science Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China Wuxi Institute of Technology Nanjing University of Information Science and Technology Jiangsu Wuxi214000 China Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China School of Computer Science Northeastern University Boston02101 United States Computer Science and Engineering The University of New South Wales SydneyNSW02101 Australia

In recent years, significant progress has been made in the development of the Rapidly-exploring Random Trees (RRT) algorithm, a probabilistic sampling-based search approach. This algorithm effectively addresses complex challenges in path planning within high-dimensional spaces characterized by intricate constraints. However, the RRT algorithm faces certain limitations, including sluggish computational performance in handling intricate calculations, susceptibility to becoming trapped in confined path regions, and difficulties in generating randomized paths across a given map. To overcome these issues, this study introduces a motion path planning method based on map reference points. Initially, the algorithm selects strategic map reference points, followed by the utilization of an enhanced RRT algorithm for fundamental path selection. Real-world scenario data is collected to empirically evaluate the algorithm’s performance. The outcomes of the experiments reveal that, within the same experimental setting, the proposed method outperforms conventional motion path planning algorithms by effectively circumventing obstacles. Furthermore, it substantially reduces the resource wastage caused by global random sampling in the RRT algorithm, leading to expedited path planning and improved pathfinding success rates. Additionally, the proposed approach enhances the RRT algorithm’s adaptability to some extent, particularly in negotiating narrow passages and intricate environments. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Catalyzing EEG signal analysis: unveiling the potential of machine learning-enabled smart K nearest neighbor outlier detection

引用

International Journal of Information Technology (Singapore) 2024年 1-12页

作者： Aymen, Abid Khediri, Salim El Thaljaoui, Adel Miladi, Moahmed Kachouri, Abdennaceur Computer & amp Embedded Systems Lab National Engineering School of Sfax University of Sfax Sfax Tunisia Department of Information Technology College of Computer Qassim University Buraydah Saudi Arabia Department of Computer Science Faculty of Science of Gafsa University of Gafsa Gafsa Tunisia Preparatory Institute for Engineering Studies of Gafsa Gafsa Tunisia Department of Computer Science and Information College of Science at Zulfi Majmaah University Al-Majmaah 11952 Saudi Arabia Higher Institute of Computer Science and Multimedia of Sfax University of Sfax Sfax Tunisia Advanced Fluid Dynamics Energetics and Environment Lab National Engineering School of Sfax University of Sfax Sfax Tunisia

Electroencephalogram (EEG) data are susceptible to artifacts, such as lapses in concentration or poor imagination, which can significantly impact the accuracy of disease diagnosis in e-health applications. To mitigate this issue, the use of machine learning (ML) and potentially artificial intelligence (AI) solutions to accurately identify outliers becomes crucial. Unlike many AI methods that incorporate unnecessary or redundant input variables, our study focuses on detecting anomalous values in EEG data through the K nearest neighbor (KNN) process and Euclidean distance metric. Our proposed unsupervised non-parametric algorithm, known as the smart KNN outlier detector (SKOD), eliminates the need for initial parameter configurations such as the number of neighbors (K), while achieving high performance. Evaluation of SKOD using real EEG data from 140 trials demonstrated sensitivity and specificity exceeding 60%, with nearly perfect accuracy in detecting outliers reaching close to 100%. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Data analysis EEG signal Healthcare Knowledge-based systems Machine learning Outlier 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：