2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)最新文献_第2页

Semi-Autonomous Control of Drones/UAVs for Wilderness Search and Rescue 半自主控制无人机/无人机野外搜索和救援

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208614

John McConkey, Yugang Liu

引用次数: 3

Digital Image Forensic Analyzer to Detect AI-generated Fake Images 用于检测人工智能生成的假图像的数字图像法医分析仪

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208613

Galamo Monkam, Jie Yan

{"title":"Digital Image Forensic Analyzer to Detect AI-generated Fake Images","authors":"Galamo Monkam, Jie Yan","doi":"10.1109/CACRE58689.2023.10208613","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208613","url":null,"abstract":"In recent years, the widespread use of smartphones and social media has led to a surge in the amount of digital content available. However, this increase in the use of digital images has also led to a rise in the use of techniques to alter image contents. Therefore, it is essential for both the image forensics field and the general public to be able to differentiate between genuine or authentic images and manipulated or fake imagery. Deep learning has made it easier to create unreal images, which underscores the need to establish a more robust platform to detect real from fake imagery. However, in the image forensics field, researchers often develop very complicated deep learning architectures to train the model. This training process is expensive, and the model size is often huge, which limits the usability of the model. This research focuses on the realism of state-of-the-art image manipulations and how difficult it is to detect them automatically or by humans. We built a machine learning model called G-JOB GAN, based on Generative Adversarial Networks (GAN), that can generate state-of-the-art, realistic-looking images with improved resolution and quality. Our model can detect a realistically generated image with an accuracy of 95.7%. Our near future aim is to implement a system that can detect fake images with a probability of odds of 1- P, where P is the chance of identical fingerprints. To achieve this objective, we have implemented and evaluated various GAN architectures such as Style GAN, Pro GAN, and the Original GAN.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122503292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Heterogeneous Graph Convolutional Network for Visual Reinforcement Learning of Action Detection 动作检测视觉强化学习的异构图卷积网络

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208414

Liangliang Wang, Chengxi Huang, Xinwei Chen

引用次数: 0

Development of Online Monitoring System for Mine Hoist Cage 矿井提升笼在线监测系统的开发

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208620

Yang Zhao, Yu Feng

引用次数: 0

Detection of River Floating Waste Based on Decoupled Diffusion Model 基于解耦扩散模型的河流漂浮垃圾检测

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208741

Changsong Pang, Yuwei Cheng

引用次数: 0

Infrared Image Transformation via Spatial Propagation Network 基于空间传播网络的红外图像变换

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208437

Ying Xu, Ningfang Song, Xiong Pan, Jingchun Cheng, Chunxi Zhang

{"title":"Infrared Image Transformation via Spatial Propagation Network","authors":"Ying Xu, Ningfang Song, Xiong Pan, Jingchun Cheng, Chunxi Zhang","doi":"10.1109/CACRE58689.2023.10208437","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208437","url":null,"abstract":"In recent years, there has been an increasing demand for intelligent infrared recognition methods. As current high-precision intelligent recognition algorithms like deep networks largely rely on massive amounts of training data, the lack of infrared databases has become a major limitation for technological development, resulting in an urgent demand for intelligent infrared image simulation technology. Different from most infrared image simulation techniques which expand infrared data amount under conditions of thermal balance, this paper proposes a novel way to simulate infrared images, i.e. generating infrared images for objects in scenes under an unsteady heat conduction process along the time axis. To be specific, this paper incorporates a spatial propagation network structure to predict the equivalent thermal conductivity coefficients for the input infrared image captured at a certain time point, and then infers the infrared images at the next time points by simulating the physical heat conduction process based on the predicted conductivity coefficients. We carry out extensive experiments and analysis on the datasets composed of factual infrared photos and PDE-simulated images, demonstrating that the proposed infrared image generation method can realize the transformation simulation and dataset expansion of infrared images with high speed and high quality.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128404939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

System Design and Workspace Optimization of a Parallel Mechanism-Based Portable Robot for Remote Ultrasound 基于并联机构的便携式远程超声机器人系统设计与工作空间优化

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10209058

Zhaokun Deng, Xilong Hou, Mingrui Hao, Shuangyi Wang

{"title":"System Design and Workspace Optimization of a Parallel Mechanism-Based Portable Robot for Remote Ultrasound","authors":"Zhaokun Deng, Xilong Hou, Mingrui Hao, Shuangyi Wang","doi":"10.1109/CACRE58689.2023.10209058","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10209058","url":null,"abstract":"The robotic ultrasound system has the potential to improve the conventional practice of diagnosing. Because of the adequate degrees of freedom embedded in a small footprint, the parallel mechanism-based ultrasound robot has attracted attention in the field. However, the analysis of its configuration, design parameters, and workspace is limited. To solve this issue and further promote the potential clinical translation, this paper proposes a task-driven, two-stage mechanism optimization method using the effective regular workspace and the local condition index to determine the parameters for the demanding clinic workspace of a parallel mechanism-based ultrasound robot. The design and implementation method of the robot are then introduced, along with the justification of parameter selection. To analyze the performance, an optical tracking-based experiment and a phantom-based human-robot comparison study were performed. The results show that the workspace meets the required clinical needs, and despite its small footprint, the mechanism could have a reasonable workspace. The kinematic error was found to be 0.2 mm and 0.3°. Based on the above results and the quantitative analysis of the ultrasound images acquired manually and robotically, it was concluded that the robot can effectively deliver the demand function and would be a promising tool for further deployment.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127649317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Motion/Force Transmission Characteristics and Good Transmission Workspace Identification Method of Multi-drive Parallel Mechanism 多驱动并联机构运动/力传递特性及良好传动工作空间辨识方法研究

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208310

Ming Han, Wangwang Lian, Dong Yang, Tiejun Li

{"title":"Research on Motion/Force Transmission Characteristics and Good Transmission Workspace Identification Method of Multi-drive Parallel Mechanism","authors":"Ming Han, Wangwang Lian, Dong Yang, Tiejun Li","doi":"10.1109/CACRE58689.2023.10208310","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208310","url":null,"abstract":"This paper puts forward a novel parallel mechanism with multiple driving modes to address the inherent limitations of workspace and singular configurations in single-driven parallel mechanisms. Taking the planar 6R parallel mechanism as an example, we conduct numerical and simulation-based studies to demonstrate the superior kinematic performance of the multi-drive mode parallel mechanism. The analytical process involved initial investigation and characterization of the mechanism, development of prototype, establishment of inverse kinematics model and introduction of local transmission index. Motion/force transmission indices under both single driving mode and multiple driving modes were then compared and analyzed. Drawing on the motion/force transmission index, we identified the good transmission workspace of the mechanism and performed a performance comparison analysis. The results unequivocally demonstrate that engaging the multi-drive mode substantially enhances the parallel mechanism's kinematic performance.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126895664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3D Scanning Vision System Design and Implementation in Large Shipbuilding Environments 大型造船环境下三维扫描视觉系统的设计与实现

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208324

Hang Yu, Yi-xi Zhao, Ran Zhang, Haiping Guo, Chongben Ni, Jin-hong Ding

引用次数: 0

Crime-Intent Sentiment Detection on Twitter Data Using Machine Learning 利用机器学习对Twitter数据进行犯罪意图情感检测

2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE) Pub Date : 2023-07-01 DOI: 10.1109/CACRE58689.2023.10208384

B. Bokolo, Ebikela Ogegbene-Ise, Lei Chen, Qingzhong Liu

引用次数: 0