检索结果-内蒙古大学图书馆

International Conference on computer, information and Telecommunication Systems (CITS)

作者： Adnan Nadeem Muhammad Ashraf Amir Mehmood Muhammad Shoaib Siddiqui Hani Almoamari Qammer H. Abbasi Faculty of Computer and Information Systems Islamic University of Madinah Madinah Kingdom of Saudi Arabia Department of Physics Federal Urdu University of Arts Science and Technology Karachi Pakistan Department of Computer Science and Information Technology Sir Syed University of Engineering and Technology Karachi Pakistan James Watt School of Engineering University of Glasgow Glasgow United Kingdom

The Kingdom of Saudi Arabia is one of the world's leading fresh date producers. Identifying damaged date palm trees on the farm is important for saving water and stopping the spread of pest which has caused the damage. In this paper, we aim to evaluate the performance of IoT-based thermal image camera input for the automatic detection of damaged trees in a Date Tree farm. The thermal images will be obtained by an IoTbased thermal camera attached to UAV. Then the temperature histogram vector will be generated which will be fed to the SVM for identification of the damaged tree. The system will raise the alarm along with the coordinates of the damaged tree for the farmer to proactively deal with the issue. The initial results of the tested scenario are encouraging for its detailed implementation in the future.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Current Trends and Emerging Challenges in Scale Imbalance Problem Object Detection

SSRN

引用

SSRN 2022年

作者： Aziz, Lubna Salam, Sah bin Haji School of Computing Faculty of Engineering University of Technology Malaysia Malaysia Computer Engineering Balochistan University of Information Technology Engineering and Management Sciences Balochistan Quetta Pakistan

1.1AbstractCurrently, handcrafted feature engineering is being replaced by deep learning-based models, which has given a tremendous boost to development of object detection technology. Object detection has become one of the most important and emerging application areas of deep learning. Object detection process is essentially based on one question like "what object is where in a given image"? Medical analysis and decision making, self-driving cars, surveillance, remote sensing technology etc. are some of prominent areas where this technology has been used. Nevertheless, with the divergence in deep learning-based object detection applications, imbalance problem is become a new research area to optimize the object detection training model. This paper mainly analyzes deep-learning based approaches to solve the scale imbalance problem in object detection. This type of imbalance usually occurs at two levels: feature level and Bounding box/ object level. This paper analyzes the main issues related to scale imbalance problem, and reviews the classical remedies that have been developed so far to address this imbalance in object detection. Through analysis, this paper discusses future research directions of object detection scale imbalance problem. © 2022, The Authors. All rights reserved.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Assessing Student Visual Fatigue in Virtual Semiconductor Labs via Head-Mounted Displays: A computer Vision Syndrome Questionnaire (CVS-Q)

Assessing Student Visual Fatigue in Virtual Semiconductor La...

引用

Sciences and Techniques of Automatic Control and computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Ahmed Jamah Ahmed Alnagrat Rizalafande Che Ismail Abubaker Almintisir Abubaker Akeel Asma Almkhtar Miftah Alhaj Salem Salah Eldeen Ali Saad Khalefah Syed Zulkarnain Syed Idrus Department of Communication Department of Computer Science and Information Technology Faculty of Business & Communication (FPK) Universiti Malaysia Perlis (UniMAP) Higher Institute of Science and Technology Kangar Perlis Malaysia Wadi al-Shati Fezzan Libya Faculty of Electronic Engineering Technology (FTKEN) Universiti Malaysia Perlis (UniMAP) Arau Malaysia Department of Mathematics and Computer Faculty of Education Wadi Alshatti University Fezzan Libya Department of Computer Science and Information Technology Higher Institute of Sciences and Technology Tripoli Libya Department of Computer Science and Information Technology Higher Institute of Science and Technology Fezzan Libya Department of Communication Faculty of Business & Communication (FPK) Universiti Malaysia Perlis(UniMAP) Kangar Perlis Malaysia

This paper evaluates visual fatigue among students in a virtual semiconductor lab using HMDs - the HP Reverb G2 and Oculus Quest 2 - and the CVS-Q questionnaire. The study measures the frequency of visual fatigue symptoms (never, occasionally, or always) and aims to determine the effects of HMD usage on visual fatigue and eye strain, providing insight into the benefits and drawbacks of using HMDs in virtual labs. The study was conducted during the COVID-19 pandemic and aims to determine the effects of HMD usage on visual fatigue and eye strain among students in a virtual semiconductor laboratory learning environment. The results of this evaluation will provide insight into the potential benefits and drawbacks of HMD usage in virtual laboratory environments and inform the development of strategies to mitigate visual fatigue.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fuzzy-Based Weighted Federated Machine Learning Approach for Sustainable Energy Management with IoE Integration

Fuzzy-Based Weighted Federated Machine Learning Approach for...

引用

2024 Systems and information engineering Design Symposium, SIEDS 2024

作者： Ghazal, Taher M. Iqbal Janjua, Jamshaid Abbas, Sagheer Fatima, Areej Saleem, Muhammad Khan, Muhammad Adnan Alqarafi, Abdulrahman Khalifa University Centre for Cyber Physical Systems Computer Science Department Abu Dhabi United Arab Emirates Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Selangor Malaysia National College of Business Administration and Economics School of Computer Sciences Lahore Pakistan Al-Khawarizmi Institute of Computer Science Lahore Pakistan Bahria University Department of Computer Science Lahore Pakistan LGU Department of Computer Science Lahore Pakistan Minhaj University School of Computer Science Lahore Pakistan Skyline University College School of Computing Sharjah United Arab Emirates Riphah International University Riphah School of Computing and Innovation Lahore Pakistan Taibah University College of Computer Science and Engineering Medina42353 Saudi Arabia

ISBN: (纸本)9798350385144

The considerable surge in energy consumption due to population growth and the use of new technology has posed significant challenges to energy security and the environment. Managing energy consumption on the consumer side is crucial as the demand for energy continues to increase. Consumers need to monitor their daily usage and understand consumption standards to prepare themselves for energy efficiency and cost savings. To address these challenges, a Smart Energy Management System (SEMS) based on the Internet of Energy (IoE) has been developed. This system uses day-Ahead planning and accurate energy availability forecasting to manage energy demand in a smart environment with high sustainable energy penetration. The Fuzzy based Weighted Federated Learning (FWFML) approach is integrated into the system to optimize energy management. The SEMS system monitors energy usage at the user level, and a review of management plans has been introduced to improve energy efficiency in terms of 93.5% accuracy, and 6.5% miss-rate. This research work also highlights future challenges in developing SEMS to increase energy efficiency in a more robust manner. © 2024 IEEE.

关键词： Energy management systems

来源：评论

学校读者我要写书评

暂无评论

Improving Accuracy and Speed of Deep Learning Algorithms for Real-Time Data Analysis in Machine Learning

Improving Accuracy and Speed of Deep Learning Algorithms for...

引用

Paradigm Shift in information Technologies with Innovative Applications in Global Scenario (ICPSITIAGS), IEEE International Conference on

作者： Fatima M. Inamdar Mahendra Kumar Singar Preeti Naval Ashutosh Pattanaik M.P. Santhoshkumar Maheswaran S Department of Information Technology Vishwakarma Institute of Information Technology Pune INDIA Department of Civil Engineering Vivekananda Global University Jaipur India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Mechanical Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Karnataka India Department of Computer Science and Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai-127 Department of Electronics and Communication Engineering Kongu Engineering College Erode Tamil Nadu INDIA

ISBN: (数字)9798350329773

ISBN: (纸本)9798350329780

This have a look at examines using deep learning algorithms for stepped forward accuracy and velocity in real-time facts evaluation in gadget studying. The goal is to offer a comprehensive assessment of recently developed optimization strategies for deep gaining knowledge of algorithms, as well as techniques to enhance their accuracy and overall performance. Additionally, the paper evaluates the potential of deep learning algorithms for actual-time information analysis, in phrases of their accuracy, pace, reliability, and scalability. In the end, the paper offers a survey of to be had datasets for deep learning, and gives hints for in addition studies. The results of this examine suggest that deep mastering algorithms can be used to enhance accuracy and speed of system getting to know for actual-time data evaluation, and that further studies must attention on exploring the ability of optimization techniques for accomplishing higher accuracy and pace.

关键词： Deep learning Knowledge engineering Surveys Machine learning algorithms Scalability Software algorithms Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Case Study: A tool for classification of system model parameters

Case Study: A tool for classification of system model parame...

引用

2021 Zooming Innovation in Consumer Technologies Conference, ZINC 2021

作者： Hlavsa, Nikola Vidovic, Ivan Dukic, Miodrag Cetic, Nenad RT-RK Institute for Computer Based Systems Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia University of Novi Sad Faculty of Technical Sciences Novi Sad Serbia

ISBN: (纸本)9781665404174

With the technological progress of the automotive industry, electronics in the car is becoming increasingly important, and thus the number of electronic control units is increasing. A2L files contain relevant information about ECU objects such as characteristics and measurement variables. As part of this paper, the creation of an XCP (Universal Measurement and Calibration Protocol) generator in C++ is presented. It is a tool for classification of system model parameters that generate A2L files. These files are used for calibration and communication with ECUs via XCP. It was based on the existing tool in Python and realized in 3 steps: first, the database and the parser model are created, then the serialized model (***) is replaced with the mentioned database, and finally, the XCP generator is written in the C++ programming language. After creating a new solution, A2L files are generated and successfully launched on the MotionWise board which uses Tricore TC297 B-Step and Renesas Electronics R-Car H3 microcontrollers. © 2021 IEEE.

关键词： Calibration

来源：评论

学校读者我要写书评

暂无评论

Solar Photovoltaic Panels Detection Using Machine Learning Algorithms

Solar Photovoltaic Panels Detection Using Machine Learning A...

引用

Electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Dania Salameh Riham Dannoun Isra Zawahra Mutaz Rasmi Abu Sara Jawad H Alkhateeb Sameh Taqatqa Mohammad Kanan Faculty of Engineering and Information Technology Palestine Ahliya University Bethlehem Palestine College of Computer Engineering and Science Prince Mohammad Bin Fahd University Khobar Saudi Arabia University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798350373363

ISBN: (纸本)9798350373370

Solar Photovoltaic Panels Detection Using Machine Learning Algorithms. This research paper deals with designing and developing algorithms capable of automatically recognizing small-sized solar photovoltaic arrays in light of high-resolution atmospheric data. Achieving this automatic recognition is crucial to provide a faster and lower-cost alternative for obtaining vital in-formation about small solar, such as geographic location, capacity, and energy production efficiency. This paper exploits machine learning algorithms to achieve the most of aerial data. This research aims to provide an effective solution that improves efficiency and accuracy in identifying and inspecting small solar photovoltaic arrays. By using a dataset of measurements of aerial images, this research presents a variety of machine-learning algorithms that aim to verify whether the measurements of an object captured in the image are identical to a polygon measurement. The research begins by presenting the linear regression algorithm, the random forest algorithm, the decision tree algorithm, and the KNN algorithm. The results indicate that the linear regression algorithm significantly outperforms other algorithms, highlighting its promising potential in identifying solar cell arrays.

关键词： Machine learning algorithms Accuracy Linear regression Solar energy Nearest neighbor methods Data models Decision trees

来源：评论

学校读者我要写书评

暂无评论

Investigative Study on Routing Protocols in Flying Ad Hoc Networks Environment 5

Investigative Study on Routing Protocols in Flying Ad Hoc Ne...

引用

5th International Conference on engineering technology and its Applications, IICETA 2022

作者： Hassan, Mustafa Hamid Abbas, Ali Hashim Mutar, Mohammed Hasan Jubair, Mohammed Ahmed Rashid, Sami Abduljabbar Ahmed, Ahmed Jamal Habelalmateen, Mohammed I. Mohammed, Aymen Audah, L. College of Information Technology Imam ja'Afar Al-Sadiq University Department of Computer Technical Engineering Al-Muthanna 66002 Iraq Al-Maarif University College Department of Computer Engineering Techniques Al-Anbar Iraq College of Technical Engineering Islamic University Department of Computer Technical Engineering Najaf54001 Iraq Al-Farahidi University Engineering Technical College Baghdad Iraq Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Batu Pahat Malaysia

ISBN: (纸本)9781665472159

In recent years, new networking paradigms such as Vehicular Ad Hoc Network (VANET), Flying Ad-hoc Networks (FANETs), and SEANETs have emerged as a result of Mobile Ad-Hoc Networks (MANETs). UAVs are gaining popularity as they are used in large-scale real-time applications. When UAVs are linked together, they form a FANET, which works collectively and in the most efficient manner possible. FANETs are designed to be used in a wide range of missions and rapidly changing scenarios. As a result, given the nature of the applications and services used to deploy UAVs, efficient routing protocols are essential. Other routing protocols, on the other hand, have been developed to date, each with its own set of limitations. This research investigates the AODV, DSDV, and AOMDV routing protocols in the context of a FANET. In terms of delay, the DSDV exceeds the other protocols, whereas the AOMDV outperforms the others in terms of average TP and PDR. © 2022 IEEE.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Technique for Sign Language Detection

Deep Learning-Based Technique for Sign Language Detection

引用

information technology Research and Innovation (ICITRI), International Conference on

作者： Zuriani Mustaffa Nik Ahmad Farihin Mohd Zulkifli Mohd Herwan Sulaiman Ferda Ernawan Yagoub Abbker Adam Faculty of Computing Universiti Malaysia Pahang Pekan Pahang Malaysia Faculty of Electrical and Electronics Engineering technology Universiti Malaysia Pahang Pekan Pahang Malaysia Universitas Nusa Mandiri Depok Indonesia Faculty of Computer Science & Information Technology Jazan University

Sign languages are a form of communication used by the deaf and hard-of-hearing community. Malay Sign Language (MSL) is the official sign language practiced in Malaysia, enabling communication through hand signs and facial expressions. Each sign and its combination hold a distinct meaning, making it challenging for individuals to casually learn MLS. Therefore, this study presents an object detection model that utilizes the Single Shot Detector (SSD) and Mobilenet to detect MLS in real time. The model focuses solely on detecting static signs that do not involve complex combinations. The datasets used for training consist of 2000 sign images collected from Kaggle website, as well as images captured using a personal camera. The datasets were divided into training, validation, and testing phases in an 80:10:10 ratio, respectively. In conclusion, this study successfully developed a real-time and accurate system for recognizing MSL using the SSD-Mobilenet model. This contribution has significant implications for the field of sign language recognition and can greatly improve communication access for individuals who are deaf or hard-of-hearing.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Augmenting Content Retrieval Through Machine Learning

Augmenting Content Retrieval Through Machine Learning

引用

Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Pavan P S T. Sripriya Vikas B Shivank Yuvraj Parmar Kalyan Acharjya Department of Civil Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Ramnagar Karnataka India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai-127 Department of Computer Engineering Vishwakarma Institute of Information Technology Pune INDIA Department of Computer Science & Engineering Vivekananda Global University Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

gadget getting to know is a subset of synthetic intelligence that focuses on making predictions via reading and getting to know patterns from records. In current years, machine studying has been increasingly more carried out to numerous fields consisting of natural language processing, laptop vision, and records analytics. in the field of content material retrieval, system gaining knowledge of strategies are used to enhance the effectiveness and efficiency of search algorithms, making it less complicated for customers to discover the information they ***, content retrieval structures depend on indexing and key-word-based totally strategies to retrieve applicable information. even as these strategies have been powerful, they have barriers in dealing with complicated queries and information the context of the facts being searched for. this is where machine learning is available in, providing the functionality to research and learn from big amounts of facts to enhance the accuracy and relevance of search consequences. through the usage of machine getting to know, content retrieval systems can better recognize the purpose at the back of a person's query and generate more correct outcomes. that is accomplished through strategies such as natural language processing, which allows the system to recognize and extract which means from text and speech. moreover, gadget gaining knowledge of can be carried out to study from past person interactions and feedback to continuously enhance the search enjoy.

关键词：

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：