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检索条件"任意字段=International Conference on Advances in Science, Engineering and Robotics Technology"

共 47866 条记录，以下是1461-1470 订阅

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Quantum Computing Odyssey: Teleporting to the Realm of Unparalleled Possibilities

Quantum Computing Odyssey: Teleporting to the Realm of Unpar...

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2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Laad, Meena Varshney, Pankhuri Agarwal, Reeti Symbiosis Institute Of Technology Department Of Applied Science Pune India

ISBN: (纸本)9798350364828

This paper delves into the exploration of quantum mechanics in the world of computing. It touches on the history of quantum computing from its first envisioning to some of the current advancements made by various major companies. The paper also discusses the numerous limitations of classical computation such as the approaching physical limit of transistors, failure in efficiency of optimization and high level problems and inability in simulation of physics. Following this, the fundamentals that are essential in understanding quantum computing such as the concepts of quantum bits, their properties of superposition and entanglement, quantum gates and quantum algorithms are covered. Further the topics that are relevant in practical utilisation of quantum computers such as various techniques to construct qubits and challenges in present day quantum systems. Finally the paper concludes with the future potential of quantum computers and their intersection with domains such as Artificial Intelligence, drug discoveries, etc. © 2024 IEEE.

关键词： Quantum entanglement

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An Improved YOLOv8 Algorithm for Oriented Object Detection in Remote Sensing Images 6

An Improved YOLOv8 Algorithm for Oriented Object Detection i...

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6th international conference on robotics and Computer Vision, ICRCV 2024

作者： Yu, Jie Huang, Wei Shen, Wei School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9798331527426

Remote sensing target detection is faced with the problems of random target direction, difficult detection of small targets, and dense arrangement. In order to solve the above problems, we propose a lightweight rotating remote sensing target detection algorithm based on YOLOv8, namely Slim-YOLOR. Firstly, we reduce the number of feature map channels in the feature fusion module, and incorporate a large kernel convolutional spatial attention (LSA) module to increase the model sensing field. Secondly, dynamic upsampling is used to reduce the information loss in the process of small target feature reconstruction and enhance the detection ability of dense small targets. Finally, the shared convolution is used to interact with the classification and regression tasks, and the deformable convolution is combined to enhance the localization of the oriented target. Experimental results on the DIOR-R dataset demonstrate that compared to YOLOv8, Slim-YOLOR reduces the number of parameters by 39.5% while increasing the mAP@O.5:0.95 by 1.6%. Additionally, Slim-YOLOR shows clear advantages over other classical algorithms. © 2024 IEEE.

关键词： Optical remote sensing

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Multi-Pedestrian Detection using Hybrid ML Algorithms for Autonomous Vehicles

Multi-Pedestrian Detection using Hybrid ML Algorithms for Au...

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2023 international conference on Recent advances in science and engineering technology, ICRASET 2023

作者： Mukherjee, Satyaki Sharma, Tanya Singh, Anshika Gayathri, S.S. Dhanalakshmi, Samiappan College of Engineering and Technology Department of Electronics and Communication Engineering Kattankulathur India

ISBN: (纸本)9798350306927

Forecasting vulnerable road user behavior is a prerequisite for the real-world implementation of Autonomous Driving Systems (ADS). The purpose of a pedestrian crossing should be detected instantaneously, particularly while driving in towns. This paper aims to detect multiple pedestrians and other automobiles while driving specifically on Indian Roads in real-time. Recent research suggests that vision-based models utilizing deep neural networks are useful for this purpose. For this paper we aim to develop an end-to-end pedestrian intention detection architecture that works well both during the day and at night. The main approach for the project is based on bounding boxes for object identification. using various deep learning techniques like YOLOv3, Darknet-53 and YOLOv7. © 2023 IEEE.

关键词： Autonomous vehicles

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MR Meets robotics: A Review of Mixed Reality technology in robotics 6

MR Meets Robotics: A Review of Mixed Reality Technology in R...

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6th international conference on robotics, Control and Automation (ICRCA)

作者： Yu, Jiawei Wang, Tengyue Shi, Yunze Yang, Liangjing Zhejiang Univ Zhejiang Univ Univ Illinois Urbana Champaign Inst Haining Peoples R China

ISBN: (纸本)9781665481748

The rising interest in Mixed Reality (MR) technology in robotics and the lack of prior work in the literature of this subject motivate this review paper. Our purpose is to discuss current research and the advancement of MR applications in the context of robotics. Development in modern robots towards a more human-centric role is driven largely by enabling technology including, but not limited to, machine vision, cobots, virtual reality, and more recently, MR technology. The scope encompasses MR technology in various aspects of robotics, namely, robot vision, control and planning, human-robot interaction, multi-user collaborations, and swarm robotics. Through discussions of the benefits and knowledge gaps in contemporary development, the review is expected to provide readers with an in-depth appreciation of the state-of-the-art technology and the possibility of MR technology in robotics.

关键词： mixed reality robotics visualization teleoperation and control

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AI-Based Bolt Loosening Diagnosis with Deep Learning from Laser Ultrasonic Wave Data

AI-Based Bolt Loosening Diagnosis with Deep Learning from La...

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2024 IEEE international conference on Big Data and Machine Learning, ICBDML 2024

作者： Arangarajan, M. Yadav, Amar Pal Veena, Ch Sasthi Kumar, C. Patel, Gaurang A. Sahu, Dillip Narayan Shri Angelman College of Engineering and Technology Department of Mechanical Engineering Tamil Nadu Tiruchirappalli India Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Engineering Dundigal Hyderabad India Organization - Karpagam Academy of Higher Education Department of Computer Science Coimbatore India Chandubhai S. Patel Institute of Technology Charotar University of Science & Technology Department of Mechanical Engineering Gujarat India Gangadhar Meher University Department of MCA Odisha India

ISBN: (纸本)9798350374100

Deep learning (DL) algorithms for non-destructive evaluation (NDE) are becoming more popular, especially for the use of laser ultrasonic methods to identify and estimate looseness in bolted joints. By examining the connection between the energy lost by the passage of ultrasound waves and the bolt head-plate's genuine contact area, this work advances the field. The study used ultrasonic wave travel imaging to produce a 3D full-field sonar dataset utilizing an acoustic emission camera and a Q-switched Nd: YAG pulsating laser. The research also highlighted how crucial signal processing methods are to improving DL performance for automated looseness estimate. © 2024 IEEE.

关键词： Yttrium aluminum garnet

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User Interface and User Experience Design Methodologies and Evaluation Techniques: A Systematic Literature Review 1

User Interface and User Experience Design Methodologies and ...

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1st IEEE international conference on advances in Computing, Communication and Networking, ICAC2N 2024

作者： Raj, Gaurav Chakraverti, Ashish Kumar Mehta, Shruti N. Sharda University Department of Computer Science & Engineering School of Engineering & Technology Greater Noida India

ISBN: (纸本)9798350356816

Effective User Interface (UI) and User Experience (UX) design are essential for digital applications, crucial for enhancing user interactions and engagement. Developing a high-quality UI is now a key aspect of software development. This study presents a comprehensive literature review of recent research on UI and UX design methodologies for digital products. It serves as the preliminary findings for an ongoing research project aimed at using this knowledge to develop a mobile game. The qualitative analysis insights are expected to significantly improve user interaction and experience in digital applications. © 2024 IEEE.

关键词： User centered design

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Real-Time 3D Bounding Box Estimation with RCNN-Resnet101 and Adaptive Projection Matrices 4

Real-Time 3D Bounding Box Estimation with RCNN-Resnet101 and...

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4th international conference on advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Kumar, Utsav Parihar, Pratik Vaithiyanathan, Dhandapani Manigandan, Muniraj National Institute of Technology Delhi Department of Electronics and Communication Engineering Delhi110036 India Vellore Institute of Technology School of Electronics Engineering Chennai India

ISBN: (纸本)9798350343670

In recent years, there has been a surge in demand for precise object detection and 3D bounding box estimation across various applications in computer vision, ranging from autonomous driving to robotics and augmented reality. This paper introduces a method specifically designed for real-time 3D bounding box estimation using a monocular camera. In contrast to conventional approaches that directly estimate 3D bounding boxes, our method begins by calculating accurate 2D bounding boxes. Subsequently, it employs a combination of mathematical modelling to predict 3D bounding boxes. The primary goal of this research is to deliver a practical and efficient solution for achieving accurate 3D bounding box estimation, capitalizing on the widespread availability of monocular camera hardware. Within our study, we independently generate the Projection Matrix, ensuring the robustness and applicability of our method across diverse datasets. This underscores the effectiveness of our approach in accurately estimating 3D object properties. Notably, our methodology demonstrates satisfactory results on both the Kitti and Cityscapes datasets, further emphasizing its proficiency in accurately estimating 3D object properties. © 2024 IEEE.

关键词： 2D to 3D Bounding Box Autonomous Navigation Depth Estimation Object Detection Single Shot Detection

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LIO-DOR: A Robust LiDAR Inertial Odometry with Real-time Dynamic Object Removal

LIO-DOR: A Robust LiDAR Inertial Odometry with Real-time Dyn...

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2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Mao, Lingjian Gao, Wei Chen, Haoyao Zhang, Shiwu University of Science and Technology of China School of Engineering Science Department of Precision Machinery and Precision Instrumentation Anhui Hefei230026 China Harbin Institute of Technology Shenzhen College of Mechanical Engineering and Automation Guangdong Shenzhen518055 China

ISBN: (纸本)9798350325706

To achieve better simultaneous localization and mapping (SLAM) under dynamic environments, this paper presents a novel robust pipeline for efficiently removing dynamic objects from the point cloud acquired by LiDAR scans. The proposed method realizes dynamic object identification through clustering cloud points and computing the collision volume between the same cluster from consecutive scans. The dynamic object removal is achieved at object level instead of point level, which ensures purer maps for subsequent path planning and navigation tasks. Extensive experiments are performed both indoors and outdoors using the open-source M2DGR dataset and a self-made dataset. The experimental results demonstrate that the proposed method outperforms mainstream SLAM methods in dynamic environments. © 2023 IEEE.

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Detecting Selected Neurodegenerative Diseases Through Microwave technology: Modeling and Identifying Different Stages of Alzheimer's Disease 6

Detecting Selected Neurodegenerative Diseases Through Microw...

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6th international Youth conference on Radio Electronics, Electrical and Power engineering, REEPE 2024

作者： M Abdel-Aleim, M. Hassan, Mohamed Mohamed, Fathy Abo Sree Ahram Candian University Faculty of Engineering Department of Electronics and Communications Engineering Cairo Egypt Arab Academy for Science Technology and Maritime Transport Department of Communication and Electronics Cairo Egypt

ISBN: (纸本)9798350382891

This research significantly advances a comprehension of the intricate complexities surrounding neurodegeneration and the associated challenges. It not only elucidates these hurdles but also imparts valuable insights into the pragmatic applications of portable microwave sensors. The proposed radiofrequency (RF) antenna, derived from this investigation, holds considerable promise for the non-invasive identification of Alzheimer's disease (AD). Its potential lies in its ability to discern subtle alterations in dielectric properties, effectively identifying instances of brain atrophy associated with AD. The innovative nature of this suggested RF antenna has the potential to revolutionize medical diagnosis and monitoring, addressing the intricate aspects of neurodegenerative disorders. This represents a substantial stride forward in this approach to understanding, detecting, and managing these complex conditions, signifying progress in the ongoing efforts to navigate the challenges posed by neurodegenerative diseases. © 2024 IEEE.

关键词： Diagnosis

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A Comprehensive Approach to Identify Stroke based on Real-time Medical Data 1

A Comprehensive Approach to Identify Stroke based on Real-ti...

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1st IEEE international conference on Cognitive robotics and Intelligent Systems, ICC - ROBINS 2024

作者： Maragatharajan, M. Shanmugapriya, S. Sudhan, M.B. Deeptha, R. Paramasivam, Sankar Muthu Vit Bhopal University School of Computing Science and Engineering Madhya Pradesh Kothrikalan India Kalasalingam Academy of Research and Education School of Computing Department of Computer Science and Engineering Tamilnadu Srivilliputhur India Srm Institute of Science and Technology Department of Computer Science and Engineering RamapuramTamilnadu Chennai India Srm Institute of Science and Technology Department of Information Technology RamapuramTamilnadu Chennai India Palo Alto Networks Inc Distinguished Software Engineer 3000 Tannery Way Santa ClaraCA United States

ISBN: (纸本)9798350372748

Strokes or cardiovascular disorders continue to be a major global health concern. Proactive intervention and timely detection greatly reduce the morbidity and death related to strokes. The goal of this research is to build a prediction model using machine learning techniques to assess a person's risk of stroke based on a variety of sociodemographic and health characteristics. The dataset used in this study consists of a large collection of medical records. It contains important details including age, gender, BMI, smoking habits, heart disease, hypertension, and the type of residential property. Using this information, a Decision Tree Classifier is trained to predict the likelihood of strokes, enabling early detection and customized treatment plans. A Decision Tree Classifier with a predetermined maximum depth is used in the proposed methodology's rigorous data preprocessing, which includes handling missing values, encoding categorical features, and developing models. Both the training and testing datasets are used to evaluate the model's performance using evaluation measures including accuracy, precision, and recall. The model's insights provide important characteristics that influence the prediction of stroke risk, assisting medical professionals in focused risk assessment and preventive intervention. The proposed method has the potential to improve healthcare practices by facilitating prompt interventions and personalized treatment for stroke risk individuals. The proposed model has resulted in 86.78% accuracy for this dataset by using the traditional machine learning algorithms. This work highlights the value of predictive modelling in the healthcare industry by demonstrating how it may improve early detection techniques and lessen the impact of strokes on public health. © 2024 IEEE.

关键词： Forecasting

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