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

共 47828 条记录，以下是991-1000 订阅

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Dynamic-DETR: Dynamic Perception for RT -DETR 6

Dynamic-DETR: Dynamic Perception for RT -DETR

引用

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

作者： Wei, Jianghao Shen, Wei Hu, Tao Liu, Qiang Yu, Jie Huang, Jiahuan School of Computer Science and Engineering Wuhan institute of Technology Wuhan China

ISBN: (纸本)9798331527426

Object detection is a crucial branch of computer vision. RT-DETR, a recent advancement building upon DETR, has showcased superior performance over YOLO in real-time object detection. However, RT-DETR may struggle with complex inputs due to its limited dynamic perception. To address this, we propose Dynamic-DETR, an enhanced object detection algorithm characterized by its dynamic and flexible nature. In the backbone stage, we introduce the ideas of adaptive dilation and deformability to enable the model to adapt to complex scale variations and geometries;in the neck stage, we introduce content-aware feature reassembly to further enhance the dynamic perception of the model. Experiments have shown that our model outperforms RT -DETR in the 2D supervised object detection task on the KITTI and SODA10M datasets. © 2024 IEEE.

关键词： Object recognition

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A Multisensory Neural Network System for Cross-modal Integration 8

A Multisensory Neural Network System for Cross-modal Integra...

引用

8th IEEE international conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Song, Yang Li, Guoxin Feng, Ying University of Science and Technology of China Department of Automatio Hefei230026 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China College of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798350300178

In the paper, we proposed a multi-sensory neural network with cross-modal integration. By distributing multiple sensors and integrating a hierarchical biomimetic architecture, our system can sense, process, and memorize multi-modal information and fuse multi-sensory data at software levels. We develop the LCMER (Learning Cross-Modality Encoder Representations) framework to build multi-modal information connections, where a multi-modal fusion model uses a single-stream model fusion. We build the LCMER model using a software system to realize hand gesture recognition. The experimental results demonstrate that the proposed LCMER framework can achieve superior gesture recognition performance in multiple scenarios. © 2023 IEEE.

关键词： Integration

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Quantum-Driven Big Data Processing

Quantum-Driven Big Data Processing

引用

2024 international conference on advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Handa, Devansh Nikhil, Kindi Krishna Duvarakanath, S. Murali, K. Amrita School Of Computing Amrita Vishwa Vidyapeetham Department Of Computer Science And Engineering Bengaluru India Amrita School Of Engineering Amrita Vishwa Vidyapeetham Department Of Mathematics Bengaluru India

ISBN: (纸本)9798350371567

The proposed study realizes a novel quantum machine learning (QML) architecture that allows heuristic function evaluation and can actually perform quantum circuits during massive data processing. The Quantum-Circuit fusion or the Quantum-Data fusion approach to information technology is the latest strategy revolutionizing the major applications with vast computing needs in present time. Our method, which is task - agnostic, is aimed to increase the machine operations speed and scale as the concepts of quantum computing are applied. In this research article, the theoretical background and perspectives are described, so generally, the idea of the combination of quantum circuits is clarified. The research delivery shows as well of this combination as its importance and possibilities, offering a new and cool method in the competitive era of data-driven computational sciences, especially in the field of quantum machine learning. Within classical machine quantum-circuit fusion the potential capability to handle a large data set and obtain the new viewpoints consequently quantum machine learning progress represents a promising route. © 2024 IEEE.

关键词： Timing circuits

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Deep Learning Based FOD Detection For Runway Health Monitoring 1

Deep Learning Based FOD Detection For Runway Health Monitori...

引用

1st international conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Kumar, Amarjeet Mittal, Aanya Dixit, Abhishek Agrawal, Pooja School of Robotics Defence Institute of Advanced Technology Pune India Manipal University Jaipur Department of Computer Science Rajasthan India Defence Institute of Advanced Technology Department of Aerospace Pune India

ISBN: (纸本)9798350355611

This paper focuses on the safety of airport runways, which is crucial for aviation industries. Foreign Object Debris (FOD) i.e. objects like nails or bolts can cause significant harm to aircraft and potentially lead to catastrophic incidents and fatalities. This study delves into detecting objects on runways by using versions of the YOLO (You Only Look Once) model. Further, it also presents the differences in detecting objects and comparing the accuracy across a range of objects, paying attention to their ability to identify even the smallest things that have a potential danger. In order to identify the model variation and enable real-time runway surveillance, the proposed methodology considers the trade-off between detection speed and precision. The results illustrate the effectiveness of the latest YOLO model in object recognition over existing models, this can support the improvement of runway safety and the development of automated systems that monitor runway conditions. © 2025 IEEE.

关键词： Aircraft accidents

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Augmented Reality for Public Engagement in Sustainable City Planning: Cloud and Machine Learning Integration

Augmented Reality for Public Engagement in Sustainable City ...

引用

2024 international conference on advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Sabitha, R. Gowriswari, S. Yuvaraj, S. Gayathri Devi, M. Babuji, R. Murugan, S. Rajalakshmi Engineering College Department Of Computer Science And Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department Of Instrumentation And Communication Engineering Tamil Nadu Chennai India Srm Institute Of Science And Technology Faculty Of Engineering And Technology Department Of Electronics And Communication Engineering Kattankulathur Tamil Nadu Chennai India Department Of Biomedical Engineering Tamil Nadu Rasipuram India R.M.K. Engineering College Department Of Electronics And Communication Engineering Tamil Nadu Chennai India Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Department Of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350371567

This paper explores how the convergence of augmented reality (AR), cloud computing, and machine learning might transform public engagement in sustainable city planning in today's dynamic urban environment. Citizens may experience proposed urban developments in unprecedented detail, including their possible social, environmental, and infrastructural impacts, due to the use of augmented reality. The potential for AR, cloud computing, and Support Vector Machines (SVM) to dramatically increase citizen participation in green urban design is investigated. With AR, individuals may explore potential new developments in virtual cityscapes. Intricate linkages within the dynamic dataset created during public participation are captured by the system's usage of SVM to evaluate and understand user comments. The ability of SVM to deal with non-linear patterns is crucial to gleaning useful insights from stakeholders' complex and varied contributions. In order to ensure that all parties involved in a system have access to the most up-to-date information, cloud computing plays a crucial role by enabling real-time collaboration and changes to the AR models This all-encompassing method not only improves the effectiveness of eco-friendly city planning, but also encourages openness and participation in policymaking. The suggested system represents a paradigm shift, demonstrating that innovative technology may be combined with informed citizenry to produce ecologically responsible and socially dynamic cities. © 2024 IEEE.

关键词： Support vector machines

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Early Detection of Diabetes Using ML Based Classification Algorithms 13th

Early Detection of Diabetes Using ML Based Classification Al...

引用

13th international Advanced Computing conference, IACC 2023

作者： Ashisha, G.R. Mary, X. Anitha Chowdhury, Subrata Karthik, C. Choudhury, Tanupriya Kotecha, Ketan Electronics and Instrumentation Engineering Karunya Institute of Technology and Science Tamil Nadu Coimabtore India Robotics Engineering Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore India Computer Science and Engineering Sreenivasa Institute of Technology and Management Studies Andhra Pradesh Chittoor India Robotics Engineering Jyothi Enngineering College Kerala Cheruthuruthy India Maharashtra Pune412115 India Maharashtra Pune412115 India

ISBN: (纸本)9783031567025

This article introduces a method for classifying diabetes based on machine learning (ML) methods. In recent years, significant focus have been put onto increasing disease classification performance through the use of ML approaches. This paper outlines the use of five interpretable ML algorithms: Bagging classifier, Random Forest, AdaBoost, Multilayer Perceptron, and Restricted Boltzmann Machine. All the ML classifiers were trained and tested in a benchmark Biostat Diabetes Dataset using Python programming. Each technique’s performance is evaluated to discover which has the finest accuracy, precision, recall, F1-score, specificity, and sensitivity. Experimental findings and assessment reveal that the Random Forest technique outperforms all other ML techniques by achieving 98% precision, 98% recall, 98% F1-score, 75% sensitivity, 96% specificity, and accuracy of 97.5%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Multilayer neural networks

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Exploring Research Opportunities to Apply Data Mining Techniques in Software engineering Lifecycle 1

Exploring Research Opportunities to Apply Data Mining Techni...

引用

1st international conference on advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Anitha Gracy, J. Parthasarathy, S. Bagavathilaksmi, R. Thiagarajar College of Engineering Applied Mathametics and Computational Science Madurai India VELS Institute of Science Technology and Advanced Studies Department of Computer Application/Information Technology Chennai India

ISBN: (纸本)9798350342796

This Software engineering (SE) is the core research area of the software industry, and numerous algorithms and frameworks are proposed every day. Software engineering is the discipline that keeps up with recent developments in fields and techniques such as data mining, machine learning, natural language processing, and artificial intelligence. It is difficult to manage such a massive amount of data in a software engineering repository if data processing and big data analytics are not available. This paper provides an in-depth study of data mining techniques that to improve the efficiency of the software development lifecycle. The study emphasizes the practical applications and discoveries made by text mining, clustering, classification, and other methods. © 2023 IEEE.

关键词： Classification Clustering Data Mining SDLC Software engineering Text Mining

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Design and validation of a novel tracheal intubation robot

Design and validation of a novel tracheal intubation robot

引用

2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Luo, Jingjing Tian, Yu Wang, Hongbo Wang, Jiawei Zhou, Luyan Tang, Jianhao Zhu, Xing Feng, Lili Han, Yuan Li, Wenxian Fudan University Institute of Ai and Robotics Academy for Engineering and Technology Shanghai210043 China Jihua Laboratory Guangdong Foshan528200 China Ministry of Education Engineering Research Center of Ai and Robotics Shanghai210043 China Eye & Ent Hospital of Fudan University Shanghai200031 China Shanghai Clinical Research Center for Aging and Medicine Shanghai200040 China Shanghai Intelligent Robot Engineering Technology Research Center Shanghai200433 China

ISBN: (纸本)9798350325706

Tracheal intubation is a crucial measure to ensure smooth respiration during general anesthesia surgeries. Currently, manual intubation is commonly employed, with its success heavily reliant on the proficiency of the physicians performing the procedure. In this paper, a 3 degree-of-freedom (DOF) master-slave operated tracheal intubation robotic system is proposed, wherein a flexible endoscope serves as the end effector. The structural components of the master-slave mechanism are described in detail, and the kinematic model of the flexible endoscope is established. Four participants were recruited to conduct experimental research on master-slave operation intubation. In the experiment, the shortest operation time recorded was 8.88 seconds, while the longest is 72.04 seconds, they are less than the clinically required safety threshold of 2 minutes. This validates the feasibility of the developed prototype in achieving robot-assisted intubation. © 2023 IEEE.

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Dynamic Performance Analysis and Experimental Research of a Spherical Robot 3

Dynamic Performance Analysis and Experimental Research of a ...

引用

3rd international conference on Control and Intelligent robotics, ICCIR 2023

作者： Shengju, Sang Yueying, Wu Bin, Feng Mingchao, Jia Zhe, Li School of Information Science and Technology Taishan University Tai'an271000 China School of Information Science and Engineering University of Jinan Jinan250000 China

ISBN: (纸本)9781510671867

A novel driving principle of electromagnetic driven Spherical robot is proposed, combining the two principles of changing the center of mass and conservation of angular momentum, and a prototype of electromagnetic driven Spherical robot is developed. In this paper, the prototype is taken as the research object, and the dynamic analysis is carried out on its climbing ability. To improve the dynamic performance of the spherical robot, the influencing factors of the dynamic performance of the spherical robot are studied: one is the ratio of the equivalent pendulum mass m of the spherical robot to the total mass (M+m) of the spherical robot, and the other is the length of the equivalent pendulum of the spherical robot the ratio of r to the radius R of the spherical robot. Then the maximum climbing angle model of the spherical robot is deduced. The experimental results show that the design of the spherical robot is reasonable and the dynamic analysis is effective. © 2023 SPIE.

关键词： Pendulums

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EFNQL: An Efficient Method Based On Q-learning And Fuzzy Neural Networks In Robocup Soccer Simulation

EFNQL: An Efficient Method Based On Q-learning And Fuzzy Neu...

引用

2023 international conference on Frontiers of robotics and Software engineering, FRSE 2023

作者： Wang, Lepeng Tan, Zhiqiu Liu, Jiangyi Yang, Yinze Central South University School of Computer Science and Engineering Changsha China

ISBN: (纸本)9798350301113

Robocup Soccer Simulation is considered to be one of the world's most prestigious and large-scale robotics events, attracting researchers from all over the world. In Robocup Soccer Simulation 2D, the challenge has always been to organize intelligent agents to collaborate and analyze scenarios in order to develop more effective strategies for launching shots and dribbling. To address this challenge, an efficient algorithmic architecture called EFNQL has been developed that utilizes fuzzy control, fuzzy neural networks, and Q-learning to optimize the strategy of the agents in Robocup Soccer Simulation competitions. The architecture first establishes fuzzy rules using fuzzy control theory, then processes more complex information on the playing field using fuzzy neural networks, and finally completes fuzzy reasoning by applying Q-learning related theory for learning. Through extensive experimentation, this thesis found that the scoring rate and ball control rate were significantly improved, ultimately resulting in a second-place finish at the 2022 RoboCup China Open. © 2023 IEEE.

关键词： Fuzzy neural networks

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