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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68649 条记录，以下是441-450 订阅

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Application and Research of Vision Inspection in the Position Self-compensation System of Industrial Robot

Application and Research of Vision Inspection in the Positio...

引用

international conference on computer Vision, Robotics, and automation Engineering, CRAE 2024

作者： Li, Yuan Lai, Pengbin Jiang, Peng Feng, Lulu He, Ruoshi School of Advanced Manufacturing Guangdong Songshan Polytechnic Shaoguan512126 China College of Automation Science and Engineering South China University of Technology Guangzhou510640 China Ministry of Science and Technology Guangdong Songshan Polytechnic Shaoguan512126 China School of Artificial Intelligence and Electrical Engineering Guangzhou College of Applied Science and Technology Guangzhou511370 China

ISBN: (纸本)9781510682283

Automatic production is closely linked with industrial robots. However, the precision of robot positioning significantly impacts the stability of the automation system. To address this issue, we establish an industrial automation system comprising an industrial camera, visual processing software, controller, and industrial robot to enable robot self-compensation. The system's visual detection module, comprising visual processing software and an industrial camera, detects offsets and compensates for errors in the industrial robot. This facilitates self-inspection and self-correction of robot grasping errors, enhancing the operational stability of the automatic production *** experimental results show that this method has strong practicability. Compared with the system without self-compensation, the steady-state error is reduced by 0.01 mm in 1000 times of repeated grabbing, which improves the stability of automatic production and has high popularization and application value. © 2024 SPIE.

关键词： Industrial robots

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An Intelligent Lubricating Oil Quality Detector Integrating computer technology 4

An Intelligent Lubricating Oil Quality Detector Integrating ...

引用

4th international conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Ouyang, Lifang Huang, He Yang, Xiaomei Hunan Finance and Economics Industry Vocational and Technical College Hunan Hengyang421002 China

This paper introduces a kind of intelligent lubricating oil quality detector integrating computer technology. On the basis of the traditional lubricating oil quality detection, through the introduction of advanced computer technology, the equipment realizes the automation of the detection process, the intelligence of data processing and the convenience of remote monitoring and management. This paper not only expounds the system structure and working principle of the detector, but also discusses the application of computer technology in the detection process. © 2024 The Authors.

关键词： Data handling

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Automated Moisture Monitoring and Irrigation Vehicle for Smart Agriculture 2

Automated Moisture Monitoring and Irrigation Vehicle for Sma...

引用

2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Femi, D. Rahman, Habeeb K.T. Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Avadi India

ISBN: (纸本)9798350340235

The population of the world is around 8 billion and it is projected to increase with average growth rate of 8.5 percent each year. This means that we need to produce more food for the survival, but the decrease in the availability of freshwater has been a barrier to it. Traditional way of irrigation requires farmers to intervene. In order to reduce the usage of water in the sector of agriculture, this paper talks about a way to monitor the moisture level of the soil in each crop and providing the required water to the crops using an automated vehicle. The vehicle is automated using Arduino Programming Board. It follows a pre-drawn line to navigate through the agriculture sector. © 2023 IEEE.

关键词： Arduino Sensor Vehicle

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A Comparative Study of Pre-trained CNNs and GRU-Based Attention for Image Caption Generation 5

A Comparative Study of Pre-trained CNNs and GRU-Based Attent...

引用

5th international conference on Robotics and computer Vision, ICRCV 2023

作者： Khan, Rashid Huang, Bingding Hassan, Haseeb Zaman, Asim Ye, Zhongfu University of Science and Technology of China Hefei College of Big Data and Internet SZTU Shenzhen China College of Big Data and Internet SZTU Shenzhen China College of Health Sciences and Environmental Engineering SZTU Shenzhen China Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei China

ISBN: (纸本)9798350326369

Image captioning is a challenging task involving generating a textual description for an image using good computer vision and natural language processing techniques. This paper proposes a deep neural framework for image caption generation using a GRU-based attention mechanism. Our approach employs multiple pre-trained convolutional neural networks as the encoder to extract features from the image and a GRU-based language model as the decoder to generate descriptive sentences. To improve performance, we integrate the Bahdanau attention model with the GRU decoder to enable learning to focus on specific image parts. We evaluate our approach using the MSCOCO and Flickr30k datasets and show that it achieves competitive scores compared to state-of-the-art methods. Our proposed framework can bridge the gap between computer vision and natural language and can be extended to specific domains. © 2023 IEEE.

关键词： computer vision

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Design of a Capsule Robot System for Gastric Hemorrhage Detection using Luminol 20

Design of a Capsule Robot System for Gastric Hemorrhage Dete...

引用

20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Mao, Yuchen Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Application Complicated Systems Intelligent Robot Laboratory School of Electrical Engineering and Automation Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

Gastric hemorrhage in upper gastrointestinal bleeding is an obvious indicator of deteriorating gastric disease. This paper proposes a capsule robot system for detecting bleeding in the stomach. The patient ingests a capsule robot containing luminol reagent, which detects bleeding in the stomach via chemiluminescence. The MCU receives the optical sensor signal, and the data is transmitted via radio frequency. The external lower computer receives and forwards the data to the upper computer for processing and display. The data is used to determine the presence and amount of stomach bleeding. Chemiluminescence is an excellent sensor, requiring no external energy supply, and demonstrating excellent sensitivity and selectivity. Combining chemical and electronic sensors presents opportunities for further development. Capsule robot detection reduces the discomfort and risk of secondary injury associated with traditional endoscopy. This paper establishes an experimental platform using porcine blood to simulate human blood, demonstrating the feasibility of the system. © 2023 IEEE.

关键词： Chemiluminescence

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Detection of TB from Chest X-ray: A Study with EfficientNet

Detection of TB from Chest X-ray: A Study with EfficientNet

引用

2023 international conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Rama, A. Rajakumar, M.P. Mythili, N. Arunmozhi, S. Mohammed, Mazin Abed Rajinikanth, V. Saveetha School of Engineering Simats Department of CSE TN Chennai602105 India St.Joseph's College of Engineering Department of Artificial Intelligence and Data Science TN Chennai600119 India St.Joseph's Institute of Technology Department of Computer Science and Engineering TN Chennai600119 India Manakula Vinayagar Institute of Technology Department of Electronics and Communication Engineering TN Puducherry605 107 India College of Computer Science and Information Technology University of Anbar Department of Artificial Intelligence Anbar31001 Iraq Saveetha School of Engineering Simats Division of Research and Innovation Department of Computer Science and Engineering TN Chennai602105 India

ISBN: (纸本)9798350315127

The lung is one of the prime organs, and any disease in the lung causes mild to severe breathing problems;untreated lung disease will lead to several complications. Tuberculosis (TB) is a lung ailment that needs premature recognition and handling. The primary objective is to employ the deep-learning (DL) based TB detection using chest $X$-rays. Various stages of the proposed scheme consist of (i) data collection and resizing, (ii) DL-supported feature extraction, (iii) binary classification and five-fold cross-validation, and (iv) comparison with earlier results and confirming the merit of the scheme. This research implements EfficientNet (EN) variants to classify the chosen $\mathrm{X}$-rays into healthy/TB classes using the SoftMax classifier. The proposed scheme with EN_B2 (ENB2) has been successful in providing an accuracy of $96{\% }$ as far as detection accuracy is considered when compared to other methods. The superiority of the suggested strategy is also confirmed by an analysis using the most recent technology, which confirms the worth of the proposed system on the chosen $\mathrm{X}$-ray imagery. © 2023 IEEE.

关键词： Deep learning

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AMAN Case Study 9th

AMAN Case Study

引用

9th international conference on Rigorous State-Based Methods (ABZ)

作者： Palanque, Philippe Campos, Jose Creissac Univ Toulouse III Paul Sabatier Interact Crit Syst Grp Toulouse France Univ Minho Dept Informat Braga Portugal INESC TEC HASLab Braga Portugal

ISBN: (纸本)9783031331626;9783031331633

This document presents the case study for the ABZ 2023 conference. The case study introduces a safety critical interactive system called AMAN (Arrival MANager), which is a partly-autonomous scheduler of landing sequences of aircraft in airports. This interactive systems interleaves Air Traffic Controllers activities with automation in AMAN. While some AMAN systems are currently deployed in airports, we consider here only a subset of functions which represent a challenge in modelling and verification.

关键词： Interactive systems formal methods Case study automation AMAN Air Traffic Control

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Cloud Based Hostel Facility automation System 1

Cloud Based Hostel Facility Automation System

引用

1st international conference on Computational Intelligence, Communication technology and Networking, CICTN 2023

作者： Agrawal, Sneha Rastogi, Sugandh Trivedi, Shivani Abes Engineering College Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798350338027

Hostel facility management system is a cloud based system was developed to automate hostel administration. The safety of their child is the top concern for parents who send their kids to hostels, whether it's for college or for other purposes. The entire process might be digital to make things simpler to observe. It will check the cleaning status of rooms, allocate rooms to students online, and give additional capabilities that will increase transparency. It controls the database's data and retrieves it as needed. The created solution supposedly addresses the shortcomings of manual hostel management and is undependable, user-friendly, and efficient. There will be usage of cloud and MongoDB technologies. In order to eliminate manual paperwork, this study is centeredon the development of a hostel automation system based on cloud computing. To reduce concurrency, all hostel activities will be administered on a single platform. © 2023 IEEE.

关键词： Office buildings

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Comparative Study of Recursive and Non-Recursive Approach in TREE Traversal

Comparative Study of Recursive and Non-Recursive Approach in...

引用

2023 international conference on IoT, Communication and automation technology, ICICAT 2023

作者： Srusti, G. Varsha, M. Guruprasad, N. Global Academy of Technology Department of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350302820

Tree traversal is a technique which involves visiting, verifying, and updating each node in a tree just once. This paper gives insight on the various approaches for the same. The tree can be visited in two ways recursively and non-recursively. This paper initiates an exploratory analysis between recursive and non-recursive algorithms for inorder, preorder, and postorder traversals. The execution time and the space-time complexity are analysed. Although the recursive approach performs efficiently in accordance with the time complexity. The non-recursive approach is given more weightage for specific occasions. In this frame of reference, this paper offers to answer the pertinent questions - which approach performs better? and when to use which approach? This paper can not only serve as a guide for researchers but also for programmers who aim on storing information and representing hierarchical data but also throws light on providing efficient algorithms for insertion, deletion, and searching. © 2023 IEEE.

关键词： inorder non-recursive postorder preorder spacetime complexity

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Container Position Detection technology Based on Stacker 3D Vision 3

Container Position Detection Technology Based on Stacker 3D ...

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3rd international conference on computer science and Blockchain, CCSB 2023

作者： Zhang, Huayu Cui, Xiang College of Mechanical and Electronic Engineering Shandong University of Science and Technology Shandong Qingdao China

ISBN: (纸本)9798350359077

In order to meet the demand of container transportation in port and realize the automation of container stacking function by stacker height machine, this paper proposes a container position detection method based on three-dimensional vision. Firstly, the container lock hole point cloud data is collected by depth camera, and then the discrete points are eliminated by using point cloud straight pass filtering and point cloud statistical filtering. The lock hole point cloud contour features are obtained by Random sample consensus (RANSAC) point cloud fitting plane algorithm, point cloud plane projection and edge extraction algorithm based on normal vector constraints, and the offset and deflection angle are calculated by using the geometric relationship of the three-dimensional coordinates of the centre point of the lock hole. Finally, the stability, real-time performance and detection accuracy of the method are verified by the experimental platform, and it is concluded from the experimental results that the method can meet the demand of automated handling of containers in ports. © 2023 IEEE.

关键词： Image processing

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