检索结果-内蒙古大学图书馆

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Constantin Patsch Eckehard Steinbach School of Computation Information and Technology Technical University of Munich Department of Computer Engineering Chair of Media Technology Munich Institute of Robotics and Machine Intelligence (MIRMI)

Segmenting activities in untrimmed videos remains a critical challenge to fully understand complex human activity sequences. A correct representation of temporal action relations is key for improving incorrect segmentations. We propose a self-attention-based model that refines initial segmentations by separately considering intra-as well as inter-segment relations between predicted action segments. Furthermore, in order to enhance the training process, we use a similarity-guided regularization technique that ensures intra-segment similarity and the validity of action transitions between adjacent segments. In an extensive evaluation on three public datasets -Georgia Tech Egocentric Activities, 50Salads, and Breakfast -our proposed architecture enhances the backbone model by 6.1% on GTEA, 3.8% on 50Salads, and 3.9% on Breakfast with regard to the F 1@50 metric.

关键词： Training Measurement Speech recognition Signal processing Predictive models Acoustics Speech processing

来源：评论

学校读者我要写书评

暂无评论

HPF-SLAM: An Efficient Visual SLAM System Leveraging Hybrid Point Features

HPF-SLAM: An Efficient Visual SLAM System Leveraging Hybrid ...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Xin Su Sebastian Eger Adam Misik Dong Yang Rastin Pries Eckehard Steinbach Department of Computer Engineering School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence (MIRMI) Chair of Media Technology Technical University of Munich Germany Siemens Technology Munich Germany Nokia Munich Germany

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Visual SLAM is an essential tool in diverse applications such as robot perception and extended reality, where feature-based methods are prevalent due to their accuracy and robustness. However, existing methods employ either hand-crafted or solely learnable point features and are thus limited by the feature attributes. In this paper, we propose incorporating hybrid point features efficiently into a single system. By integrating hand-crafted and learnable features, we seek to capitalize on their complementary attributes in both key-point identification and descriptor expressiveness. To this purpose, we design a pre-processing module, which includes extraction, inter-class processing, and post-processing of hybrid point features. We present an efficient matching approach to exclusively perform the data association within the same class of features. Moreover, we design a Hybrid Bag-of-Words (H-BoW) model to deal with hybrid point features in matching and loop-closure-detection. By integrating the proposed framework into a modern feature-based system, we introduce HPF-SLAM. We evaluate the system on EuRoC-MAV and TUM-RGBD benchmarks. The experimental results show that our method consistently surpasses the baseline at comparable speed.

关键词： Visualization Simultaneous localization and mapping Accuracy Extended reality Semantics Benchmark testing Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

引用

computer Systems Science & engineering 2023年第5期45卷 1711-1726页

作者： Manar Ahmed Hamza Aisha Hassan Abdalla Hashim Dalia H.Elkamchouchi Nadhem Nemri Jaber S.Alzahrani Amira Sayed A.Aziz Mnahel Ahmed Ibrahim Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt College of Science and Humanities Studies in Alquwayiyah Shaqra UniversitySaudi Arabia

Wireless Sensor Network(WSN)consists of a group of limited energy source sensors that are installed in a particular region to collect data from the *** the energy-efficient data collection methods in largescale wireless sensor networks is considered to be a difficult area in the *** node clustering is a popular approach for ***,the sensor nodes are grouped to form clusters in a cluster-based WSN *** battery performance of the sensor nodes is likewise *** a result,the energy efficiency of WSNs is *** specific,the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station(BS).Therefore,energy efficiency and load balancing are very essential in *** the proposed method,a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques(GW-IPSO-TS)was *** selection of Cluster Heads(CHs)and routing path of every CH from the base station is enhanced by the proposed *** provides the best routing path and increases the lifetime and energy efficiency of the ***-to-end delay and packet loss rate have also been *** proposed GW-IPSO-TS method enhances the evaluation of alive nodes,dead nodes,network survival index,convergence rate,and standard deviation of sensor *** to the existing algorithms,the proposed method outperforms better and improves the lifetime of the network.

关键词： Wireless sensor networks energy-efficient load balancing energy consumption network’s lifetime cluster heads grey wolf optimization tabu search particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

An Efficient Breast Cancer Detection Framework for Medical Diagnosis Applications

引用

computers, Materials & Continua 2022年第1期70卷 1315-1334页

作者： Naglaa F.Soliman Naglaa S.Ali Mahmoud I.Aly Abeer D.Algarni Walid El-Shafai Fathi E.Abd El-Samie Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt International Academy for Engineering and Media Science October CityEgypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Breast cancer is themost common type of cancer,and it is the reason for cancer death toll in women in recent *** diagnosis is essential to handle breast cancer patients for treatment at the right *** with mammography is the preferred examination for breast cancer,as it is available worldwide and ***-Aided Detection(CAD)systems are used to analyze medical images to detect breast cancer,*** death rate of cancer patients has decreased by detecting tumors early and having appropriate treatment after *** of mammogram images has four main steps:pre-processing,segmentation of the region of interest,feature extraction and classification of the images into normal or abnormal *** paper presents an efficient framework for processing of mammogram images and introduces an algorithm for segmentation of the images to detect *** pre-processing step of mammogram images includes removal of digitization noise using a 2D median filter,removal of artifacts using morphological operations,and contrast enhancement using a fuzzy enhancement *** proposed fuzzy image enhancement technique is analyzed and compared with conventional techniques based on an Enhancement Measure(EME)and local contrast *** comparison shows an outstanding performance of the proposed technique from the visual and numerical *** segmentation process is performed using Otsu’smultiple thresholding *** method segments the image regions into five classes with variable intensities using four *** effectiveness is measured based on visual quality of the segmentation output,as it gives details about the image and positions of *** performance of the proposed framework is measured using Dice coefficient,Hausdorff,and Peak Signal-to-Noise Ratio(PSNR)*** segmented tumor region with the proposed segmentation method is 81%of the ground truth region provided by an ***,the proposed framew

关键词： Breast cancer mammogram images CAD contrast enhancement fuzzy logic segmentation

来源：评论

学校读者我要写书评

暂无评论

Semi/Fully-Automated Segmentation of Gastric-Polyp Using Aquila-Optimization-Algorithm Enhanced Images

引用

computers, Materials & Continua 2022年第2期70卷 4087-4105页

作者： Venkatesan Rajinikanth Shabnam Mohamed Aslam Seifedine Kadry Orawit Thinnukool Department of Electronics and Instrumentation Engineering St.Joseph’s College of Engineering Chennai600119India Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Faculty of Applied Computing and Technology Noroff University CollegeKristiansand4608Norway Research Group of Embedded Systems and Mobile Application in Health Science College of ArtsMedia and TechnologyChiang Mai UniversityChiang Mai50200Thailand

The incident rate of the Gastrointestinal-Disease(GD)in humans is gradually rising due to a variety of reasons and the Endoscopic/Colonoscopic-Image(EI/CI)supported evaluation of the GD is an approved *** and evaluation of the suspicious section of the EI/CI is essential to diagnose the disease and its *** proposed research aims to implement a joint thresholding and segmentation framework to extract the Gastric-Polyp(GP)with better *** proposed GP detection system consist;(i)Enhancement of GP region using Aquila-Optimization-Algorithm supported tri-level thresholding with entropy(Fuzzy/Shannon/Kapur)and between-class-variance(Otsu)technique,(ii)Automated(Watershed/Markov-Random-Field)and semi-automated(Chan-Vese/Level-Set/Active-Contour)segmentation of GPfragment,and(iii)Performance evaluation and validation of the proposed *** experimental investigation was performed using four benchmark EI dataset(CVC-ClinicDB,ETIS-Larib,EndoCV2020 and Kvasir).The similarity measures,such as Jaccard,Dice,accuracy,precision,sensitivity and specificity are computed to confirm the clinical significance of the proposed *** outcome of this research confirms that the fuzzyentropy thresholding combined with Chan-Vese helps to achieve a better similarity measures compared to the alternative schemes considered in this research.

关键词： Endoscopic/colonoscopic-image gastric polyp aquila-optimizationalgorithm fuzzy entropy chan-vese segmentation

来源：评论

学校读者我要写书评

暂无评论

Practical Performance of a Distributed Processing Framework for Machine-Learning-based NIDS

Practical Performance of a Distributed Processing Framework ...

引用

IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Maho Kajiura Junya Nakamura Department of Computer Science and Engineering Toyohashi University of Technology Toyohashi Japan Information and Media Center Toyohashi University of Technology Toyohashi Japan

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Network Intrusion Detection Systems (NIDSs) detect intrusion attacks in network traffic. In particular, machine-learning-based NIDSs have attracted attention because of their high detection rates of unknown attacks. A distributed processing framework for machine-learning-based NIDSs employing a scal-able distributed stream processing system has been proposed in the literature. However, its performance, when machine-Iearning-based classifiers are implemented has not been comprehensively evaluated. In this study, we implement five representative clas-sifiers (Decision Tree, Random Forest, Naive Bayes, SVM, and kNN) based on this framework and evaluate their throughput and latency. By conducting the experimental measurements, we investigate the difference in the processing performance among these classifiers and the bottlenecks in the processing performance of the framework.

关键词： Support vector machines Distributed processing Fault tolerant systems Network intrusion detection Telecommunication traffic Throughput Stability analysis

来源：评论

学校读者我要写书评

暂无评论

Practical Performance of a Distributed Processing Framework for Machine-Learning-based NIDS

arXiv

引用

arXiv 2024年

作者： Kajiura, Maho Nakamura, Junya Department of Computer Science and Engineering Toyohashi University of Technology Toyohashi Japan Information and Media Center Toyohashi University of Technology Toyohashi Japan

Network Intrusion Detection Systems (NIDSs) detect intrusion attacks in network traffic. In particular, machine-learning-based NIDSs have attracted attention because of their high detection rates of unknown attacks. A distributed processing framework for machine-learning-based NIDSs employing a scalable distributed stream processing system has been proposed in the literature. However, its performance, when machine-learning-based classifiers are implemented has not been comprehensively evaluated. In this study, we implement five representative classifiers (Decision Tree, Random Forest, Naive Bayes, SVM, and kNN) based on this framework and evaluate their throughput and latency. By conducting the experimental measurements, we investigate the difference in the processing performance among these classifiers and the bottlenecks in the processing performance of the framework. Copyright © 2024, The Authors. All rights reserved.

关键词： Network security

来源：评论

学校读者我要写书评

暂无评论

Active Learning Strategies for Textual Dataset-Automatic Labelling

引用

computers, Materials & Continua 2023年第8期76卷 1409-1422页

作者： Sher Muhammad Daudpota Saif Hassan Yazeed Alkhurayyif Abdullah Saleh Alqahtani Muhammad Haris Aziz Department of Computer Science Sukkur IBA UniversitySukkur65200Pakistan Al Quwayiyah College of Sciences and Humanities Shaqra UniversityShaqra15526Saudi Arabia Self-Development Skills Department Common First Year DeanshipKing Saud UniversityRiyadh12373Saudi Arabia STC’s Artificial Intelligence Chair Department of Information SystemsCollege of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia College of Engineering&Technology University of SargodhaSargodha40100Pakistan

The Internet revolution has resulted in abundant data from various sources,including social media,traditional media,*** the availability of data is no longer an issue,data labelling for exploiting it in supervised machine learning is still an expensive process and involves tedious human *** overall purpose of this study is to propose a strategy to automatically label the unlabeled textual data with the support of active learning in combination with deep *** specifically,this study assesses the performance of different active learning strategies in automatic labelling of the textual dataset at sentence and document *** achieve this objective,different experiments have been performed on the publicly available *** first set of experiments,we randomly choose a subset of instances from training dataset and train a deep neural network to assess performance on test *** the second set of experiments,we replace the random selection with different active learning strategies to choose a subset of the training dataset to train the same model and reassess its performance on test *** experimental results suggest that different active learning strategies yield performance improvement of 7% on document level datasets and 3%on sentence level datasets for auto labelling.

关键词： Active learning automatic labelling textual datasets

来源：评论

学校读者我要写书评

暂无评论

A NOVEL MODEL FOR THE MATERIAL SELECTION OF SMART OBJECTS FOR HAND-REHABILITATION: A CASE STUDY 24

A NOVEL MODEL FOR THE MATERIAL SELECTION OF SMART OBJECTS FO...

引用

24th International Conference on engineering Design, ICED 2023

作者： Bos, Mikaël Ivar Karahanoǧlu, Armaǧan Haarman, Juliet Nizamis, Kostas Chair of Systems Engineering and Multidisciplinary Design Department of Design Production and Management Faculty of Engineering Technology University of Twente Enschede Netherlands Interaction Design Research Group Department of Design Production and Management Faculty of Engineering Technology University of Twente Enschede Netherlands Human Media Interaction Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands

Home hand rehabilitation for stroke is becoming increasingly important due to logistic and financial challenges. Developing Daily-life Integrated Hand-rehabilitation Products (DIHP) aims to enable the application of at-home rehabilitation. The materials of these products are essential for their success, however, selecting materials for DIHP has not been investigated yet. Previous research on material selection showed that it is done strictly on material properties or based on a human-centered approach. Hence, in this study, we propose a hybrid model for choosing materials for DIHP. To achieve this, we first combined the findings of previous material selection processes into a comprehensive material selection model. We applied this model in a case study, in which we first selected three materials based on their properties. Following, we 3d printed a DIHP out of the chosen materials and tested the feeling of the materials with multiple expert groups. Our findings suggest that the proposed material selection method is promising and highlights that our comprehensive model provides more insights when compared to a strict material property-based selection. © The Author(s), 2023. Published by Cambridge University Press.

关键词： 3D printing

来源：评论

学校读者我要写书评

暂无评论

Intelligent Optimization-Based Clustering with Encryption Technique for Internet of Drones Environment

引用

computers, Materials & Continua 2022年第12期73卷 6617-6634页

作者： Dalia H.Elkamchouchi Jaber S.Alzahrani Hany Mahgoub Amal S.Mehanna Anwer Mustafa Hilal Abdelwahed Motwakel Abu Sarwar Zamani Ishfaq Yaseen Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Computers and Information Computer Science DepartmentMenoufia UniversityEgypt Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo 11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

The recent technological developments have revolutionized the functioning of Wireless Sensor Network(WSN)-based industries with the development of Internet of Things(IoT).Internet of Drones(IoD)is a division under IoT and is utilized for communication amongst *** drones are naturally mobile,it undergoes frequent topological *** alterations in the topology cause route election,stability,and scalability problems in *** is considered as an effective method to transmit the images in IoD *** current study introduces an Atom Search Optimization basedClusteringwith Encryption Technique for Secure Internet of Drones(ASOCE-SIoD)*** key objective of the presented ASOCE-SIoD technique is to group the drones into clusters and encrypt the images captured by *** presented ASOCE-SIoD technique follows ASO-based Cluster Head(CH)and cluster construction *** addition,signcryption technique is also applied to effectually encrypt the images captured by drones in IoD *** process enables the secure transmission of images to the ground *** order to validate the efficiency of the proposed ASOCE-SIoD technique,several experimental analyses were conducted and the outcomes were inspected under different *** comprehensive comparative analysis results established the superiority of the proposed ASOCE-SIoD model over recent approaches.

关键词： Internet of drones atom search algorithm clustering encryption signcryption

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：