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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

共 18818 条记录，以下是381-390 订阅

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Review: controller System Design of Permanent Magnet Direct Current Motor Based on Fuzzy Logic 3

Review: Controller System Design of Permanent Magnet Direct ...

引用

3rd international Scientific conference of Engineering Sciences, ISCES 2023

作者： Salih, Khansaa Ghanim Mohammed Hussien, Enas Mohammed Al-Mustansiriyah University Department of Computer Science Baghdad Iraq

ISBN: (纸本)9798350302912

Permanent magnet direct current (PMDC) motors are widely utilized in industry for a variety of applications that call for quick and precise speed control. This article suggests a method for increasing the individually stimulated DC motor's speed. To complete this optimization procedure, the rise time, settling time, and overshoot characteristics are reduced. PID and fuzzy logic work together to implement a suitable performance after modeling the DC motor with Matlab Simulink. To control the motor speed, a fuzzy-defined weighting point approach is used. The results of the thorough simulation demonstrate that the design has improved dynamic and static performance, no overshoot, and a faster response time. For achieving highly accurate control, it performs better than traditional control methods. © 2023 IEEE.

关键词： controllers

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Visual damage detection technology for conveyor belts in coal-fired power plants 3

Visual damage detection technology for conveyor belts in coa...

引用

3rd international conference on Energy and Power Engineering, control Engineering (EPECE)

作者： Cheng, Weiliang Yin, Xinwei Wang, Yanchun North China Elect Power Univ Sch Energy Power & Mech Engn Beijing 102206 Peoples R China Datang Environm Ind Grp Co Ltd Beijing 100097 Peoples R China

ISBN: (纸本)9798350366105;9798350366099

Chinese coal-fired power plants generally use cantilever bucket wheel machines to stack and retrieve coal from their coal yards. The belt conveyor of the bucket wheel machine is the main transportation equipment for coal fuels. During the operation of a belt conveyor, the conveyor belt is prone to damage and often experiences longitudinal tearing. Once longitudinal tearing occurs, if not detected in time, it may damage the entire conveyor belt and cause huge losses to the production of coal-fired power plants. It is of great significance to develop a visual based conveyor belt damage detection technology to improve the efficiency and accuracy of fault detection for coal yard conveyor belts in coal-fired power plants, and ensure the safety of bucket wheel equipments. Long wave and medium wave infrared CCD ( Charge coupled device) cameras are used for image acquisition. After algorithmic processing of the infrared radiation intensity with the image information, it is converted into corresponding grayscale images. The traditional two-dimensional Otus image processing algorithm was optimized using the lion group algorithm, and the chaotic sequence mechanism was introduced to achieve the optimal binary image threshold segmentation. The FAST(Features from accelerated segment test) algorithm is used to discover image corners for image features and fault recognition. Based on the refinement algorithm, the longitudinal tearing defect of the images is further determined using the Hough transform. Based on this, this article proposes a vision based conveyor belt damage detection and analysis method, which overcomes the harsh environmental requirements of actual sites and adds optimization and secondary processing processes. The research results indicate that this method can effectively monitor and identify damage to conveyor belts, with recognition accuracy of over 98%, and corresponding prediction measures can be proposed to further prevent the increase of damage.

关键词： Algorithm computer vision Belt conveyor Damage detection Bucket wheel machine

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Integrated Machine vision Strategies for Enhanced Autonomous Driving Safety 24

Integrated Machine Vision Strategies for Enhanced Autonomous...

引用

3rd international conference on computer, Artificial Intelligence and control Engineering, CAICE 2024

作者： Gao, Heyang Zhang, Yi Hu, Jun Su, Menghao Cao, Jinghan Bian, Haoyu Hokkaido University Hokkaido60014652 Japan Newcastle University Newcastle60006222 United Kingdom Shanghai Jiao Tong University Shanghai60025084 China Zhongyuan University of Technology Zhengzhou60073737 China Rutgers University New Jersey United States Nanjing University Nanjing60033100 China

ISBN: (纸本)9798400716942

As intelligent transportation systems continue to advance, the integration of sophisticated machine vision technologies into autonomous driving becomes increasingly crucial. This article delves into a comprehensive approach that merges various machine vision techniques to bolster the safety features of autonomous vehicles. The focus is on three key aspects: enhancing lane-keeping capabilities, refining vehicle and lane detection algorithms, and developing proactive collision warning systems. By synthesizing state-of-the-art methods from current research, the paper presents a unified framework that not only improves the detection and tracking of road lanes and surrounding vehicles but also anticipates and alerts to potential hazards with greater accuracy and speed. The culmination of these improvements aims to significantly reduce the risk of on-road incidents, ensuring a safer autonomous driving experience. This integration represents a leap forward in the quest to resolve the complex challenges of autonomous vehicle navigation and safety, paving the way for more reliable and intelligent transportation solutions. © 2024 ACM.

关键词： Machine vision

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Machine vision-Based Sorting Robot for Courier Station 3

Machine Vision-Based Sorting Robot for Courier Station

引用

3rd IEEE international conference on Social Sciences and Intelligence Management, SSIM 2023

作者： Xie, Chunyan Liu, Zhongyuan Liang, Xulin Zhang, Bin Xie, Ying Wang, Yu School of Electronic Engineering and Automation Guilin University of Electronic Science and Technology Guilin China

ISBN: (纸本)9798350327786

To solve the current problems such as the large volume of courier business and the slow speed of manual sorting in courier stations, a machine vision-based courier sorting robot was developed in this study. The robot contained STM32 as the main controller and an Openmv camera to collect information. It adopted YOLOv5s target detection, zbar barcode recognition, PID control, robotic arm grasping, and sensors. The robot has an omnidirectional chassis structure equipped with a six-degree-of-freedom robotic arm and a two-degree-of-freedom gimbal to provide excellent maneuverability. Different from the traditional manual sorting, the sorting robot does not require staff to scan the code of the courier into the warehouse, sorting, labeling, and moving on the shelves. The courier sorting efficiency was improved with reduced labor costs. The sorting robot can be used in the logistics terminal courier station, replacing labor for courier sorting with feasibility and innovation. © 2023 IEEE.

关键词： Three term control systems

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Application of computer Intelligent Sensing Technology in Seedling Transplanting System of Small Remote control Biological Floating Island 3

Application of Computer Intelligent Sensing Technology in Se...

引用

3rd international Signal Processing, Communications and Engineering Management conference, ISPCEM 2023

作者： Deqiang, Bu Xiaorong, Zhang Jinsheng, Wang Shandong University of Engineering and Vocational Technology Jinan China

ISBN: (纸本)9798350307023

Aiming at the problems of less mechanical equipment and low efficiency of manual operation in the seedling transfer and cutting process of biological floating island technology, a small remote control seedling transplanting device of biological floating island was studied based on existing small hull equipment and rice transplanter. A combination of wireless remote control and sensing device is used to control the hull remotely, so that the stability control, speed control and steering control of the hull on the water surface can be achieved through remote operation. So that the planting mechanism can accurately transplanting seedlings into the corresponding hole position of the floating bed, and realize the accurate and efficient transplanting operation of biological floating island seedlings. © 2023 IEEE.

关键词： Remote control

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GUI Development for An Image Enhancement Application to Support computer vision 3

GUI Development for An Image Enhancement Application to Supp...

引用

3rd international conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Nasucha, Mohammad Rahmat, Revo Satrio, Muhammad Khornelius, John Bryan Hermawan, Hendi Handoko, Prio Universitas Pembangunan Jaya Center for Urban Studies Department of Informatics Tangerang Selatan Indonesia Universitas Pembangunan Jaya Department of Informatics Tangerang Selatan Indonesia

ISBN: (纸本)9798350372120

Graphical User Interfaces (GUIs) play a pivotal role in software, offering intuitive interaction with electronic devices. This paper introduces a GUI for image enhancement, aiming to simplify the process for both single and batch image operations. Developed using PySide6, the program allows users to adjust enhancement parameters easily. The methodology involves algorithm development, GUI design using Qt Designer, integration of algorithms with the GUI, and testing. Furthermore, the paper outlines the process of converting the program into an executable (.exe) file for broader accessibility. The results demonstrate the GUI's functionality in image enhancement tasks. © 2024 IEEE.

关键词： Image enhancement

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Unity 3D-Based Six-Degree-of-Freedom Robotic Arm Virtual Simulation Teaching Platform 3

Unity 3D-Based Six-Degree-of-Freedom Robotic Arm Virtual Sim...

引用

3rd international conference on Robotics, Artificial Intelligence and Intelligent control (RAIIC)

作者： Hu, Jinwen Lu, Qiuhong Fan, Haoyu Xiao, Yuntao Zhou, Youtao Zhang, Shimian Univ Elect Power Sch Automat Engn Shanghai 200090 Peoples R China Shanghai HRSTEK Co Ltd Shanghai 201102 Peoples R China

ISBN: (纸本)9798350352634;9798350352627

The robotic arm is an important foundation for robots to perform a variety of complex tasks, and the robotic arm grasping technology involves multidisciplinary and multidisciplinary fields, which leads to a high learning threshold due to reasons such as more complex and abstract theoretical knowledge. In addition, the whole set of industrial robots is expensive, and it is difficult to ensure that each experimenter is involved. To address these issues, this paper is based on the visualization of Unity3D development platform vision technology, using SolidWorks modeling, and combined with the actual scene in the robotic arm grasping operations, to achieve a highly immersive virtual simulation of a typical case of grasping the target object, to build a six-degree-of-freedom robotic arm virtual simulation teaching system;to achieve the virtual simulation teaching software and the robotic arm unit to establish communication, the The virtual simulation system is integrated with the robotic arm unit operation platform. The system has the advantages of easy operation, real simulation effect and good learning effect, which is of positive significance for improving the teaching quality and research level of robot arm related courses.

关键词： six degree of freedom manipulator forward and inverse kinematics Teaching virtual simulation

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How Deep Learning is Implemented in Manufacturing Quality control 3

How Deep Learning is Implemented in Manufacturing Quality Co...

引用

3rd international conference on Artificial Intelligence and computer Information Technology, AICIT 2024

作者： Li, Dongjin Chen, Xinyan Tan, Peiwen Jia, Jie School of Electronic Information Shanghai Dian Ji University Shanghai201306 China

ISBN: (纸本)9798350365443

This study aims to explore the application and effect of deep learning technology in manufacturing quality control. The study deployed a convolutional neural network (CNN) model to analyze images and sensor data during the manufacturing process to achieve automatic detection and classification of defects. The experiments were conducted in a simulated high-speed production line environment, and a large amount of production data, including images and sensor readings, were collected and processed. The results showed that the accuracy of the deep learning model in identifying serious, moderate and minor defects reached 98%, 95% and 90% respectively, which was significantly higher than the traditional quality control system. The conclusion shows that deep learning technology can significantly improve the quality control accuracy and efficiency of the manufacturing industry, provide strong technical support for the field of intelligent manufacturing, and indicate broad application prospects in advanced manufacturing systems that require higher levels of automation and intelligence. © 2024 IEEE.

关键词： Smart manufacturing

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Smart Agriculture: Enhancing Crop and Weed Detection Using MobileNetV2 for Autonomous Farming Systems 3

Smart Agriculture: Enhancing Crop and Weed Detection Using M...

引用

3rd international conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Uma, P. Pranav, S. Ma, Sutharson Vignesh, V. Nandha Engineering College Department of Computer Science and Engineering Erode India

ISBN: (纸本)9798331523893

Agriculture is vital to food security and economic stability, but weeds reduce crop yields by competing for sunlight, water, and nutrients. Manual weeding and herbicides are often ineffective and environmentally harmful. This study presents an autonomous weeding robot that utilizes MobileNetV2 for real-time crop and weed detection, leveraging its lightweight architecture for efficient performance on devices like the NVIDIA Jetson Nano. The system achieves 85% accuracy, a 0.72 IoU score, and 25 FPS processing speed, with field tests showing detection accuracy of up to 90% in ideal conditions. By reducing herbicide use and improving resource efficiency, this approach supports sustainable agriculture, with future advancements such as multispectral imaging and pest detection further enhancing its role in precision agriculture. © 2025 IEEE.

关键词： Weed control

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Smart Attendance By Using Face Recognition 3

Smart Attendance By Using Face Recognition

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3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Kumar, Naveen Vasantha Kumari, N. Sheetal Alli Presidency College Department of Computer Applications Bangalore India

ISBN: (纸本)9798331515911

Maintaining attendance by hand in contemporary classrooms is a laborious activity that is prone to errors and mistakes. To make this process easier to comply with, we suggest a Face Recognition Based Attendance Management System (FRAMS) which makes use of modern facial recognition technology to eliminate the need for manual attendance. This system utilizes computer vision technology where face detection and recognition take place using real time python open cv software while mingling through a comfortable user interface designed by Tkinter. Haar Cascade classifiers are incorporated for face detection while the facial recognition aspect is conducted through an efficient algorithm referred to as Local Binary Patterns Histograms (LBPH) that is resistant to changes in lighting, facial emotions and facial *** works by taking students pictures using a webcam and a dataset is generated from these pictures. This dataset is then used to prepare the face recognition model. During attendance sessions, live faces are compared against the stored database within the system to recognize and verify users. When the system is capable to identify a person, it automatically registers the person's state using the online spreadsheet which further provides attendance records in a precise manner. The aided system is efficient as it removes the need for attendants roll call, thereby minimizing errors and curtailing proxy *** so, the system was subjected to extensive testing when in use in various situations and its recognition accuracy rate was high in controlled conditions. There were, however, some problems like the differences in lighting and the chances of wrongful identification in the middle of busy pictures. Even so, in light of these challenges, FRAMS is an improvement over the attendee sheets that yesteryear utilized because it's faster and more dependable. For works in progression, it may be possible to enhance the recognition algorithms to cope with increasing

关键词： User interfaces

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