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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621-630 订阅

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High Autoencoder Based System for Seamless Transformation of Grayscale Portraits into Vibrant Color Representations

High Autoencoder Based System for Seamless Transformation of...

引用

2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Sarna, Anurag Gadwal, Ashwinee Choundawat, Jaydeep Singh Kate, Vandana Sharan, Mahima Acropolis Institute of Technology and Research Dept. of Csit Indore India

ISBN: (纸本)9798350388800

This research explores the domain of visual content transformation, focusing on the use of autoencoders to convert black-and-white images into vivid color representations. Specifically, Convolutional Autoencoders are used in conjunction with Generative Adversarial Networks (GANs), with particular emphasis on portraits, to create vibrant and contextually relevant color renditions. Deep learning techniques, including convolutional neural networks and conditional generative adversarial networks, are employed to ensure the efficiency and precision of the colorization process. The significance of this work lies in its promising applications in historical preservation, artistic expression, and storytelling. By infusing monochromatic images with renewed vitality, this research aims to enrich visual content and pave the way for a colorful era of digital storytelling. The main outcomes of this study include the development of a robust Autoencoder-based system for grayscale-to-color image conversion and the exploration of its potential impact on various fields, including art, history, and narrative communication. © 2024 IEEE.

关键词： Generative adversarial networks

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The Role of Machine Learning in Optimizing Industrial Communication Protocols

The Role of Machine Learning in Optimizing Industrial Commun...

引用

2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Kharbas, Vikas Kumar Mahesh, T.R. Upadhyay, Satish Vivekananda Global University Department of Computer Science & Application Jaipur India Faculty of Engineering and Technology Department of Computer Science Engineering Bangalore India Atlas SkillTech University Department of UGDX Mumbai India

ISBN: (纸本)9798350388800

Due to the complexity and urgency of information exchange in modern companies, optimizing communication protocols in the workplace is essential. Using methods from machine learning, this research takes a fresh tack toward optimizing the performance of communication protocols. The suggested approach integrates Reinforcement Learning (RL), Convolutional Neural Networks (CNNs), and Genetic Algorithms (GAs) to provide a self-optimizing system with dynamic behavior. The RL feature facilitates this protocol's flexibility in the face of dynamic network circumstances by providing rapid feedback. CNNs are used for real-time anomaly detection to improve safety and dependability. GAs methodically explores combinations of protocol parameters to determine the optimal collection that matches specified performance criteria. The recommended technique was compared to the usual methodology using a variety of efficiency and reliability measures. The findings demonstrate that the proposed approach frequently outperforms the state-of-the-art methods in a broad range of commercial settings with regards to efficiency, dependability, and adaptability. Understanding how to enhance industrial communication protocols is crucial in the age of Industry 4.0 and the IIoT. The recommended solution offers an autonomous, adaptable, and secure tool for boosting communication in dynamic production situations. © 2024 IEEE.

关键词： Convolutional neural networks

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Active Complaint Control for Smooth and Quick Connector Assembly

Active Complaint Control for Smooth and Quick Connector Asse...

引用

2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Wu, Jun He, Yu Wang, He Wang, Qiyu Fan, Shaowei University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

ISBN: (纸本)9798350325706

This paper presents an active complaint control for smooth and quick connector assembly. The application requirement of an end-effector with simultaneous connecters is firstly defined. Then, the hybrid impedance control provides the foundation for active search and passive assembly. After that, a resolution-variant Lissajous search is proposed for smooth motion and earlier connection. At last, simulations and experiments indicate that the proposed controller can guarantee smooth and quick search for connector assembly. © 2023 IEEE.

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Multi-Robot Consensus with Adaptive Learning-Based Dynamic Controller Updates

Multi-Robot Consensus with Adaptive Learning-Based Dynamic C...

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2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Shit, Santu Kashyap, Anshul Nandanwar, Anuj Malyshev, Dmitry Rybak, Larisa Dhar, Narendra Kumar Indian Institute of Technology Mandi H.P. Kamand175005 India Belgorod State Technological University Department of Mechanical Engineering Belgorod308012 Russia

ISBN: (纸本)9781665481090

This paper addresses the problem of dy-namic controller updates if needed to achieve consensus in a Multi-robot system (MRS) framework while en-suring overall stability. The intermittent updates allow robots to follow the leader robot, maintaining a desired separation. The theoretical developments in this work have been validated through experiments, reinforcing the practical viability of our proposed methodology. The results show the efficiency of the proposed con-troller in removing transient errors and achieving consensus easily even for a large MRS framework. © 2024 IEEE.

关键词： Adversarial machine learning

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RedSpear: Re-engineered Discharge (RED) Team Toolkit for Empowerment of Cyber Security

RedSpear: Re-engineered Discharge (RED) Team Toolkit for Emp...

引用

2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Nigam, Nidhi Panwar, Mohit Singh Kate, Vandana Vishwakarma, Aishwary Sharma, Atharva Yadav, Aman Acropolis Institute of Technology and Research Department of Csit Indore India

ISBN: (纸本)9798350388800

Cyber security is always changing, with new threats, challenges and vulnerabilities arising constantly in the digital world. This paper introduces the RedSpear Red Team Cyber Security Toolkit to help beginners and non-experts navigate this complex field. This user-friendly toolkit is designed for ease of use and accessibility. It includes features like a live host scanner, host discovery, common vulnerabilities and exposures (CVE) descriptions, directory scanner, and more. The toolkit is web- based and aims to make it simple for users to grasp the basics of red teaming. This paper also delves into the benefits of a toolkit for red teaming in the cyber security. It highlights its user-friendly interface, thorough coverage of key aspects, and how it can help users grasp the tools of the red team framework. In addition, it touches on the advantages for beginners and non- experts and suggests areas for future growth. © 2024 IEEE.

关键词： Cyber attacks

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Communication Between Submarines Using Li-Fi technology

Communication Between Submarines Using Li-Fi Technology

引用

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

作者： Shanthi, T. Shalini, P. Shahul Hameed, S. Sona College of Technology Department of Electronics and Communication Engineering Salem India

ISBN: (纸本)9798350306927

Underwater communication plays a significant role in research, engineering, and military applications. Various electromagnetic signals, including radio frequency, acoustic communication, and wireless optical communication, are currently employed for underwater communication. However, these methods have certain limitations, prompting the need for Li-Fi technology to overcome such issues. Light Fidelity (Li-Fi), uses visible light communication systems that employ light-emitting diodes to achieve medium- to high-speed transmission. This technology is used to increase data transmission speed and security, as light travels at a high speed underwater. © 2023 IEEE.

关键词： Light emitting diodes

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Enhanced Grid Map Correction Using an Improved ORB Algorithm 6

Enhanced Grid Map Correction Using an Improved ORB Algorithm

引用

6th international conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2024

作者： Ye, Aofei Wen, Shengjun Li, Hongjun Wang, Yan Liao, Liang Luo, Xiaopeng School of Automation and Electrical Engineering Zhongyuan University of Technology Zhengzhou China School of Zhongyuan-Petersburg Aviation Zhongyuan University of Technology Zhengzhou China School of Mathematics and Information Science Zhongyuan University of Technology Zhengzhou China School of Zhongyuan-Petersburg Aviation Engineering Zhongyuan University of Technology Zhengzhou China

ISBN: (纸本)9798331541699

This paper addresses the challenge of grid map accuracy errors in multi-map merging, focusing on developing a robust and consistent occupancy grid map. To enhance feature point detection, the oFAST algorithm usingadaptive thresholding is proposed, which amplifies edge responses and increases detection accuracy. Additionally, descriptors derived from local self-correlation matrices are integrated into the BRIEF algorithm to improve robustness in complex environments. Matched feature points are refined using a K-Nearest Neighbors strategy combined with distance threshold filtering, followed by RANSAC-based estimation of the homography matrix to further ensure matching precision. A correction algorithm is proposed, which adjusts the coordinates of the matched feature points and fits a correction curve, thereby refining the pixel structure of the entire grid map. The proposed algorithm is validated by experimental data. © 2024 IEEE.

关键词： MapReduce

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RBF Neural Network-Based Output Constrained Control of Servo System with LuGre Friction 6

RBF Neural Network-Based Output Constrained Control of Servo...

引用

6th international conference on robotics, Control and Automation engineering, RCAE 2023

作者： Zhao, Haibo Zhou, Xianghong Tongling University Department of Electrical Engineering Tongling China No.43 Research Institute China Electronic Science and Technology Group Company Hefei China

ISBN: (纸本)9798350315301

In order to weaken the adverse effect of friction nonlinearity on electromechanical servo system with LuGre friction, an adaptive control strategy was proposed. The LuGre friction model of servo system was first given. By introducing the stabilizing function, using backstepping approach and selecting the Barrier Lyapunov function, and adopting a radial-basis-function (RBF) neural network to design adaptive law, a RBF neural network-based output constrained backstepping adaptive controller was designed, and its stability was analyzed. Compared with the single RBF neural network control in simulation results, the proposed control strategy shows better position and speed tracking performance. © 2023 IEEE.

关键词： Servomechanisms

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Nondestructive Detection of Internal Quality of Hami Melon by Hyperspectral technology Combined with Chemometrics

Nondestructive Detection of Internal Quality of Hami Melon b...

引用

2024 lEEE international conference on Advanced Information, Mechanical engineering, robotics and Automation, AIMERA 2024

作者： Li, Fengxia Yang, Quan Wang, Xiaochen Gao, Wenjun Huang, Yong Yin, Junchi University of Science and Technology Beijing Institute of Engineering Technology Beijing China Xinjiang Institute of Engineering School of Mechanical and Electrical Engineering Urumqi China

ISBN: (纸本)9798350343335

In this research, the combination of hyperspectral technology and chemometrics was applied for non-destructive testing of the internal quality of Hami melon. Sugar content and firmness serve as crucial indicators in assessing the internal quality of this fruit. Various pretreatment methods were employed for feature extraction, and subsequently, partial least squares (PLS) prediction models were established for sugar content and firmness. The outcomes reveal that the optimal results for the PLS sugar content prediction model were achieved when utilizing the original spectrum treated with multivariate scattering correction (MSC), resulting in a correlation coefficient of 0.663 and a prediction root-mean-square error of 0.909. Similarly, the PLS firmness prediction model exhibited the best performance when based on the first derivative spectrum treated with the standard normal variable transformation (SNV), yielding a correlation coefficient of 0.674 and a prediction root-mean-square error of 6.388 N. This investigation demonstrates the feasibility of employing hyperspectral technology in combination with chemometrics for simultaneous detection of the internal quality of Hami melon. The findings of this study suggest promising prospects for the future market application of the research method. The integration of hyperspectral technology and chemometrics offers a reliable and efficient approach for non-destructive evaluation of Hami melon quality, paving the way for its potential implementation in the fruit industry to ensure enhanced product quality control and consumer satisfaction. © 2024 IEEE.

关键词： Prediction models

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Dynamic Obstacle Avoidance for Magnetic Helical Microrobots Based on Deep Reinforcement Learning

Dynamic Obstacle Avoidance for Magnetic Helical Microrobots ...

引用

2024 IEEE international conference on Real-Time Computing and robotics, RCAR 2024

作者： Qiu, Yukang Hou, Yaozhen Yang, Haotian Gao, Yigao Huang, Hen-Wei Shi, Qing Huang, Qiang Wang, Huaping Beijing Institute of Technology Intelligent Robotics Institute School of Mechatronical Engineering Beijing100081 China Harvard Medical School Laboratory for Translational Engineering CambridgeMA02139 United States Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9798350372601

Magnetic helical microrobots hold immense promise in biomedical domains owing to their compact size and efficient propulsion capabilities. However, navigating these microrobots through dynamic and unstructured environments, particularly when encountering numerous dynamic obstacles, remains a formidable challenge. In the study, a control framework based on deep reinforcement learning (DRL) with the objective of guiding a microrobot through dynamic obstacles towards specified target goals is introduced. Initially, we design and fabricate a microdrill capable of propulsion via external magnetic rotating fields produced by our magnetic actuation system. Subsequently, we construct a custom training environment, adhering to the OpenAI gym interface, to serve as the simulator for training purposes. Utilizing the proximal policy optimization algorithm, we conduct training of the navigation policy within this simulator. Simulations and experimental validations conducted in dynamic environments affirms the efficacy of the proposed method. © 2024 IEEE.

关键词： Microrobots

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