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DADN: Data Augmentation-Driven Dual Network Framework for Node Classification 2

DADN: Data Augmentation-Driven Dual Network Framework for No...

引用

2nd international conference on Automation, robotics and Computer engineering, ICARCE 2023

作者： Liu, Dengfeng Pan, Zhiqiang Wang, Siyuan Li, Peihong Liu, Shixian Mao, Yanying National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Changsha China

ISBN: (纸本)9798350308341

Node classification is an important task in graph neural networks (GNNs), aiming to predict the category of nodes in the graph according to their neighbours and their own characteristics. Current methods mainly focus on one level of data augmentation, ignoring huge potential in other underlying levels. Furthermore, existing models cannot fully exploit the information contained in the existing data, which undermines the performance of node classification. In order to solve the above problems, we propose a novel Data Augmentation-driven Dual Network (DADN) framework. Specifically, we first design a composite data augmentation module that comprehensively considers the local neighborhood level, the node level, and the edge level to augment the original features. Then, we copy the original features and the augmented features into the dual network framework with dropout for model training to capture the innermost features. Finally, we experimentally evaluate our method on three real-world public datasets, and the results show that our method outperforms the baseline models in the node classification task, except for individual metrics. © 2023 IEEE.

关键词： Classification (of information)

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Research on Time-series Visualization Methods for Scientific and Technical Consulting Graph Data

Research on Time-series Visualization Methods for Scientific...

引用

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

作者： Hu, Xinyang Wang, Lei Wei, Qiushi Shang, Jin Haihong, E. Beijing University of Posts and Telecommunications School of Computing Beijing China China Mobile Information Technology Co. Ltd Beijing China Jinze Building No.2 Guangningbo Street Xicheng District Beijing China

ISBN: (纸本)9798350301113

The existing open-source knowledge visualization components do not support knowledge graph temporal visualization exploration capabilities and cannot meet the demand of analyzing the dynamic evolutionary changes of industries in science and technology consulting scenarios. In this paper, to address the above problems, we propose a knowledge graph-based temporal visualization component construction and optimization method to build a graph visualization component that supports temporal dynamic exploration based on existing open-source knowledge visualization components to address the demand for industry insight analysis in science and technology consulting graph analysis services. At the same time, a data processing and graph rendering optimization strategy is proposed to improve the overall task execution efficiency in response to the problems of low rendering efficiency and high computational resource occupation rate in the time-series visualization exploration scenario. © 2023 IEEE.

关键词： Time series

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Attention-Guided Unsupervised Network for Image Deraining 6

Attention-Guided Unsupervised Network for Image Deraining

引用

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

作者： Deng, Zifan Xu, Junwu Yang, Shuwei School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9798331527426

Single image deraining is crucial for subsequent computer vision tasks such as object detection, scene understanding, and video analysis. Traditional deraining methods often require end-to-end learning of specific rain streak features, which suffer from poor generalization and lack an automated learning process. Moreover, rain streaks vary across different environments, obscuring and blurring background information while also introducing changes in illumination and color distortion. To address these issues, we propose an Attention-guided Unsupervised Network for Image Deraining, called AUN-ID. AUN-ID incorpo-rates an Attention-based Rain-mask Extraction Block(AREB) to accurately extract rain streaks from images. These extracted streaks are fused with the original rainy image through a Feature Fusion Block(FFB) to obtain a preliminary derained image. Subsequently, leveraging the constrained transfer learning ability and cyclic structure of CycleGAN, we reconstruct clean no-rain images of better quality. © 2024 IEEE.

关键词： Image fusion

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Fault-Tolerant Control for Delayed PDE-ODE Coupled Systems 3

Fault-Tolerant Control for Delayed PDE-ODE Coupled Systems

引用

3rd international conference on robotics, Automation and Intelligent Control, ICRAIC 2023

作者： Shi, Xi-Dong Wang, Zi-Peng Yan, Xue-Hua Zhang, Xiao-Wei University of Jinan School of Electrical Engineering Jinan China Beijing University of Technology Faculty of Information Technology Beijing China Tiangong University School of Control Science and Engineering Tianjin China

ISBN: (纸本)9798350360813

This paper introduces a fault-tolerant control strategy for delayed PDE-ODE coupled systems. By using a Lyapunov functional (LF), a fault-tolerant control design is developed by space-dependent linear matrix inequality (SDL-MI) to ensure the exponential stability (ES) for the closed-loop delayed PDE-ODE coupled system. Finally, the effectiveness of the control approach is demonstrated through its application to a hypersonic rocket car (HRC). © 2023 IEEE.

关键词： Lyapunov functions

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An Inception Transformer-CNN Architecture for Robotic Grasping Detection

An Inception Transformer-CNN Architecture for Robotic Graspi...

引用

2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Miao, Haining Xu, Xiangrong Wang, Weijing Cui, Huanhuan Rodic, Aleksandar Petrovic, Petar B. Xu, Shanshan Wang, Haiyan School of Mechanical Engineering Anhui University of Technology Anhui Ma'anshan243002 China School of Cumputer Science and Technology Anhui University of Technology Anhui Ma'anshan243002 China University of Belgrade Faculty of Mechani cal Engineering Belgrade11120 Serbia School of Osaka Medical Engineering Ma'anshan University Anhui Ma'anshan243100 China

ISBN: (纸本)9781665481090

Addressing the issue of low accuracy in detecting suitable grasping regions for unknown objects through visual information, this paper proposes an Inception Transformer-CNN architecture for robot grasping detection, referred to as ITC-Grasp. The aim is to enhance the accuracy of grasping unknown objects. The architecture incorporates an Inception mixer with a channel-splitting mechanism, integrating the powerful capability of CNN in extracting high-frequency representations into the Transformer. By synergizing the local modeling capability of CNN and the global modeling capability of Transformer, it achieves superior feature representation, thereby improving grasping detection performance. Additionally, the architecture introduces a frequency slope structure to effectively balance high and low-frequency components across different layers. The results on the Cornell dataset show that the proposed method achieves 98.2% image segmentation accuracy and 97.1% object segmentation accuracy, respectively, showing competitive performance. The feasibility and effectiveness of the proposed method are verified by simulation experiments. © 2024 IEEE.

关键词： Image segmentation

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Customer Spending Prediction on E-Commerce Website 15

Customer Spending Prediction on E-Commerce Website

引用

15th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Salake, Sudha V. Patil, Pankaja Kunchur, Pavan Bangarashetti, Sadhana Managuli, Manjunath Patil, Sheetal B. Department of Computer Science and Engg KLS Gogte Institute of Technology Belagavi India Department of Information Science and Engg Basaweshwar Engineering College Bagalkot India Department of Electronics and Communication Engineering KLS Gogte Institute of Technology Belagavi India Department of Computer Science and Engg SJB Institute of Technology Belagavi India

ISBN: (纸本)9798331300579

In the ever-evolving world of e-commerce, understanding customer behavior and predicting their spending patterns is crucial for businesses to thrive. This work presents an innovative application designed to predict customer spending on an e-commerce website. By leveraging advanced machine learning techniques and utilizing comprehensive customer data, the application offers valuable insights that can be used to optimize sales strategies and enhance customer *** application employs a robust predictive model trained on historical customer data, including purchase history, browsing patterns, demographic information, and transactional *** application incorporates real-time data updates to ensure continuous improvement and adaptability to changing customer *** proposed application offers a powerful tool for e-commerce businesses to predict customer spending, optimize sales strategies, and deliver personalized experiences. By harnessing the power of machine learning and leveraging comprehensive customer data, businesses can stay competitive in the dynamic e-commerce landscape and foster long-term customer loyalty. © Grenze Scientific Society, 2024.

关键词： Marketplaces

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Partially Observable Markov Decision Processes for Robotic Assistance in a Sensor-Fused Smart Home Environment 10

Partially Observable Markov Decision Processes for Robotic A...

引用

10th international conference on Automation, robotics, and Applications, ICARA 2024

作者： Papadopoulos, Aristeides D. Kechagia, Ioanna Giakoumis, Dimitrios Votis, Konstantinos Tzovaras, Dimitrios Information Technologies Institute Center for Research and Technology Hellas Thessaloniki Greece Aristotle University of Thessaloniki Mechanical Engineering Thessaloniki Greece

ISBN: (纸本)9798350394245

In this work the Partially Observable Markov Decision Process (POMDP) method is formulated for the determination of robot actions whose role is to assist a Human Activity Recognition (HAR) system in a smart home environment. The HAR consists of various sensors (wearable, microphones, cameras, smart plugs, temperature and humidity sensors) whose outputs are optimally fused to enhance the classification accuracy. In cases where the result of the HAR is uncertain a robot assists in the classification by approaching the person, performing its own recognition and providing, from its sensors, additional optical and audio data to the HAR. The POMDP model takes into consideration the precision of the HAR and assigns higher probability to state transitions that are more likely to occur. © 2024 IEEE.

关键词： Wearable sensors

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Research on Motion Control of Bipedal Wheeled-leg Robot Based on Distributed Model 3

Research on Motion Control of Bipedal Wheeled-leg Robot Base...

引用

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

作者： Yang, Yang Zhian, Zhang Nanjing University of Science and Technology School of Mechanical Engineering Nanjing210094 China

ISBN: (纸本)9781510671867

With the rapid development of mobile robot technology, bipedal wheeled-leg robots, which combine the efficient mobility of wheeled robots and the adaptability of legged robots to uneven terrain, are gradually attracting widespread attention. In complex terrains and unstructured environments, such as stairs, ramps, and narrow spaces, bipedal wheeled-leg robots have superior mobility and adaptability. This article introduces a motion control method for bipedal wheeled-leg robots with a five-bar leg configuration. This method decouples the robot system based on a distributed model, analyzes the body and wheeled leg system separately, and implements a controller for the robot's rapid movement on flat terrain, adaptation to unstructured terrain, and jumping movements through virtual model control and model predictive control. A series of experiments have verified the feasibility of the prototype system's movement in real-world scenarios. © 2023 SPIE.

关键词： Motion control

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A Detailed Analysis of Wavelet based Multi-Focus Image Fusion Techniques 5

A Detailed Analysis of Wavelet based Multi-Focus Image Fusio...

引用

5th international conference on Smart Electronics and Communication, ICOSEC 2024

作者： Mohamed Ali, E.A. Vinoth, M. Kalpanadevi, G. Subbulakshmi, M. Dharani, R. Jp College of Engineering Department of Electronics & Communication Engineering Tenkasi India K. Ramakrishnan College of Engineering Department of Electronics & Communication Engineering India Bannari Amman Institute of Technology Department of Artificial Intelligence & Data Science India J.J. College of Engineering and Technology Department of Electronics & Communication Engineering India

ISBN: (纸本)9798331504403

Image fusion combines multiple images of a single scene or object, captured by various sensors or from different angles, to create an enhanced composite image with greater informational content. This process has applications across diverse fields, including remote sensing, medical diagnostics, security systems, robotics, augmented reality, and stereovision. Its primary objectives include improving visual details, overall image quality, and offering novel perspectives. Among the various fusion methods, wavelet-based techniques have gained popularity due to their ability to preserve crucial details, minimize noise, and enhance visual quality. This study aims to compare the efficacy of eight distinct wavelet-based multi-focus image fusion approaches. To assess the spectral and spatial characteristics of the resulting fused images, the research employs eight performance metrics, providing a comprehensive analysis of these techniques. The findings of this comparative study are important for deciding which method is the simplest, most effective, and fastest to produce high-quality merged images. This will enable it to be used with a variety of imaging modalities, especially those that have limited hardware resources or produce images with a high level of quality. © 2024 IEEE.

关键词： Medical robotics

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Stability Analysis of Underwater engineering Remote Operated Vehicle 8

Stability Analysis of Underwater Engineering Remote Operated...

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

作者： Shang, Weiyan Chen, Xiaohu Yi, Xinhua Zheng, Wei Cao, Hongfei Ningbo University of Technology Ningbo China Hangzhou Bay Campus Department of Mechanical Engineering China

ISBN: (纸本)9798350300178

In order to improve the running performance of the underwater engineering ROV (Remote Operated Vehicle), it's stability under different swimming motion states was analyzed. Firstly, the kinematic and dynamic model of the system are established. Then the Lyapunov exponents of the ROV in the six degrees of freedom directions of roll Angle, pitch Angle, steering Angle, x, y and z axis moving were obtained. And finally, the stability of ROV under vertical, steering and direct navigation motion states driven by different thrust conditions is analyzed. The driving system of 8-thruster underwater robot is proved to be stable by simulation. © 2023 IEEE.

关键词： Degrees of freedom (mechanics)

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