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Disease Classification of Oranda Goldfish Using YOLO Object Detection Algorithm 15

Disease Classification of Oranda Goldfish Using YOLO Object ...

引用

15th international conference on computer and automation engineering, ICCAE 2023

作者： Medina, Jeanne Katherine Jasper P. Tribiana, Pete Villaverde, Jocelyn F. Mapua University School of Electrical Electronics and Computer Engineering Manila Philippines

ISBN: (纸本)9798350396225

Owning an ornamental fish aquarium at home is not easy. It requires much attention to maintain its healthy state. However, if the keeper is a beginner and unable to take care of it properly, a problem may arise. One example is Oranda Goldfish which can easily acquire fish lice, fungi, and white spots. If not recognized at a possible early time, the diseases may spread to the entire aquarium or, worse, the loss of the fish. This study aims to create a system that can diagnose fish disease accurately earlier than the conventional method. The system acquires goldfish images or live feeds using a camera module and undergoes pre-processing to emphasize the essential features. Once the features are segmented, the YOLO algorithm will extract them. The system will then classify any detected disease. The results of the data sampling were able to detect and classify the goldfish samples accurately, with an overall accuracy of 91.4286%. This study utilizing CNN and YOLO helped resolve this problem by diagnosing the common disease of the goldfish. It helps beginner fish farmers, veterinarians, aquarium owners to detect the disease at the earliest time. © 2023 IEEE.

关键词： Fish

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computer Aided Design of Lens Systems 6

Computer Aided Design of Lens Systems

引用

6th IEEE international conference on automation, Electronics and Electrical engineering, AUTEEE 2023

作者： Shen, Yuan Wang, Shengdong Liu, Dongcai Anhui Jianzhu University Hefei China Hefei Normal University Hefei China

ISBN: (纸本)9798350305623

In order to meet the standardized design requirements of lenses, a lens aided design system based on parametric modeling is designed. The development of this system makes full use of computer-aided design technology to realize the parametric design and modeling functions of lenses. Users only need to use the system before using the system. It is only necessary to have an understanding of the mirror parameters to improve the efficiency of lens design and at the same time achieve the integration of design and parameter modeling. First, the parameters of common lens surface types are introduced, and then the lens design is parametrically modeled based on optical design input, which facilitates designers to adjust the lens model and reduces the repeatability of manual operations. Based on the CAD system based on OCC, designed lenses can be optimized, edited and redesigned, which improves lens design efficiency. At the same time, incremental saving is applied to improve file update efficiency. © 2023 IEEE.

关键词： computer-aided design incremental synchronization lens design parametric modeling

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A Study of Task Offloading Strategies in IoV 6

A Study of Task Offloading Strategies in IoV

引用

6th international conference on computer Network, Electronic and automation, ICCNEA 2023

作者： Wei, Jingyun Liang, Xiangyang Xi'an Technological University School of Computer Science and Engineering Xi'an710021 China

ISBN: (纸本)9798350305388

In this paper, we study task offloading for mobile edge computing in the Internet of Vehicles (IoV). We use response time as a system performance metric and use a closed queuing network to analyze the optimal task offloading probability, which enables task offloading to have latency *** a vehicle offloads a task, there is an optimal offload probability allocation ratio so that the task has the same response time regardless of whether the task is offloaded to the cloud center or the edge layers to achieve task offload fairness. The distribution ratio to achieve fairness in task offloading is affected by the number of vehicles. Through experiments, we learn that the more vehicles there are, the more computational tasks need to be offloaded to the cloud server to achieve fairness. Also, the average response time of the edge server grows rapidly as the number of vehicles increases. © 2023 IEEE.

关键词： Vehicles

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Using Augmented Reality to enhance the experience of IoT-based Home automation Systems

Using Augmented Reality to enhance the experience of IoT-bas...

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2023 IEEE international conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Kaur, Deepti Prit Sharma, Manmohan Sharma, Preeti Malik, Garvit Mehakdeep Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of computer Science and Engineering Manipal University Jaipur Jaipur India

ISBN: (纸本)9798350305708

Internet of Things (IoT) is an integral part of home automation, where physical devices are interconnected such that, they enable communication amongst electronics, sensors, software, and network. The data collection and analysis in IoT, and unified framework in cloud computing strives to improve living standards and productive outcomes by interacting with smart devices. In various fields such as education, control, and entertainment, Augmented Reality (AR) technology attempts to improve user experiences through improved interactions within the available settings. This paper presents an IoT based Home automation System, which uses Augmented Reality as an additional technology to enable utilization of real time visualization and interaction for better experience. The application is beneficial for children, elderly and differently abled persons as it would aid them with control of electrical appliances just by scan through a device camera, connected to internet. From a safety perspective also, it offers electrical isolation. © 2023 IEEE.

关键词： Augmented Reality Home automation IoT

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An Ingenious Deep Learning Approach for Home automation using Tensorflow Computational Framework 2

An Ingenious Deep Learning Approach for Home Automation usin...

引用

2nd international conference on Electronics and Renewable Systems, ICEARS 2023

作者： Ilampiray, P. Thilagavathy, A. Sahith, Challa Sai Hari Uma Varma, Penumathsa Girish Sai Bhuvanendra Chowdary, V. Dhanush, M. R.M.K. Engineering College Department of Computer Science and Engineering Kavaraipettai India

ISBN: (纸本)9798350346640

Home automation has become an important part nowadays. Home automation and the Internet of Things are becoming popular because automatic systems are preferred by most people. Life has become easier with automation. The emerging technologies like Machine Learning (ML) and Deep Learning (DL) play a major role in home automation. Nowadays there is a tremendous growth of mobile devices. But with machine learning systems, there is an increasing demand for smartphone applications. This paper focuses on an interactive mobile application that can control household electronic devices such as fans, AC, light, Television, etc., with the help of on-device machine learning and the Internet of Things. The proposed machine-learning algorithm automatically detects the type of device in just a photo-scan and performs the basic operations. © 2023 IEEE.

关键词： Internet of things

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A Dataset and Multi-task Multi-view Approach for Question-Answering with the Dual Perspectives of Text and Knowledge 15

A Dataset and Multi-task Multi-view Approach for Question-An...

引用

15th international conference on computer and automation engineering, ICCAE 2023

作者： Adithya, M.S. Ahmed, Mohsin Kestur, Mihir Madhusudan Chaithanya, A Sai Das, Bhaskarjyothi Pes University Computer Science Engineering Bengaluru India

ISBN: (纸本)9798350396225

Question-answering (QA) systems are important tools for extracting information from large datasets and providing accurate and relevant answers to user queries. Two of the most widely studied and built QA systems are Natural Language Question Answering (NLQA) and Knowledge Graph Question Answering (KGQA). NLQA relies on sequence learning algorithms, which have limitations on the length of input they can handle, while KGQA relies on the Subject-Predicate-Object (SPO) tuple representation of data, which may not always be available in the knowledge graph. In this paper, we present a novel approach for addressing these challenges by utilizing the structural information from the Knowledge Graph (KG) and the semantic information from the Natural Language Context. Due to the lack of a dataset to enable this approach, we propose the creation of a multi-view dataset - MTL-QA, specifically designed for multi-task learning. We also present a multi-task learning approach to jointly train NLQA and KGQA models and demonstrate the effectiveness on the proposed MTL-QA dataset. © 2023 IEEE.

关键词： Semantics

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Classification of Stroke Using Machine Learning Techniques: Review Study

Classification of Stroke Using Machine Learning Techniques: ...

引用

2023 international conference on Control, automation and Diagnosis, ICCAD 2023

作者： Sawan, Aktham Awad, Mohammed Qasrawi, Radwan Al Quds University Department of Computer Science Jerusalem Palestine Arab American University Department of Computer Systems Engineering Ramallah Palestine Istinye University Department of Computer Engineering Istanbul34010 Turkey Al Quds University Jerusalem Palestine

ISBN: (纸本)9798350347074

Presently, stroke is the leading cause of adult injury worldwide. The World Health Organization estimates that each year 15 million people around the world suffer a stroke. Five million of them die, and another five million are disabled for life. There is a chance to dramatically enhance the classification of strokes in the early stages. In this article, we reviewed all portable devices that produced electroencephalogram(EEG) data and all machine learning (ML) methods and deep-learning methods used to identify stroke using EEG data, and we noted that the amount of work on ML and deep learning in analyzing EEG data have increased rapidly in recent years. Such analysis has achieved greater precision compared to that conventional methods. We also discussed in this study the opportunities and key challenges for improving the accuracy of future work. © 2023 IEEE.

关键词： Electroencephalography

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Study on the Evaluation Method of Angularity and Position Errors for Plane Features 2

Study on the Evaluation Method of Angularity and Position Er...

引用

2nd international conference on automation, Robotics and computer engineering, ICARCE 2023

作者： Zhao, Zexiang Zhao, Xinyu Li, Bin School of Mechatronics Engineering Zhongyuan University of Technology Zhengzhou China School of Computer Science Zhongyuan University of Technology Zhengzhou China Key Laboratory of Optical Sensing and Testing Technology for Mechanical Industry Zhengzhou China

ISBN: (纸本)9798350308341

The plane features of part drawings may have such indications as angularity tolerance and/or position tolerance and additional symbols. In this paper, twelve kinds of angularity tolerance drawing indications and twenty-eight kinds of position tolerance drawing indications were given, and the evaluation models of angularity error and position error were established. Based on the models above, the program for evaluating angularity errors and position errors of plane features was developed. The simulated profiles of plane features for two samples were taken as an example, and twelve cases of angularity errors and twenty-eight cases of position errors were evaluated and analyzed. The analysis of the evaluation results showed that the evaluation results of partial angularity errors and position errors are quite different under the same datum plane and the same measured object, and both datum plane and toleranced object have obvious influences on the evaluation results of angularity errors and position errors. This research may help designers understand the meanings of angularity tolerance zones, position tolerance zones and their additional symbols and indicate drawings reasonably. © 2023 IEEE.

关键词： Errors

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Infrared image enhancement algorithm based on IWGIF and WTD 4

Infrared image enhancement algorithm based on IWGIF and WTD

引用

4th international conference on Digital Signal and computer Communications, DSCC 2024

作者： Yuan, Run Li, Xisheng School of Automation and Electronic Engineering University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9781510681538

Aiming at the problems of detail loss, edge blurring and noise amplification in traditional infrared image enhancement methods, an algorithm based on improved weighted guided image filtering (IWGIF) and wavelet thresholding denoising (WTD) is proposed. The algorithm first uses IWGIF to filter and layer the input image to obtain the base layer and detail layer. For the base layer, the high-frequency component obtained through wavelet decomposition (WD) is processed through WTD and subsequently reconstructed using wavelet reconstruction (WR) along with the low-frequency component. Contrast is then enhanced by contrast limited adaptive histogram equalization (CLAHE). For the detail layer, its edge details are enhanced by gain calculation. Finally, the processed two layers are weighted and fused to obtain the enhanced image. In this paper, the algorithm is applied to images captured by infrared thermal imaging devices, and the results of the combination of subjective and objective evaluation indexes show that the method in this paper shows good performance in infrared image enhancement. © 2024 SPIE.

关键词： Wavelet decomposition

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Automatic Number Plate and Speed Detection using YOLO and CNN 9

Automatic Number Plate and Speed Detection using YOLO and CN...

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9th IEEE international conference for Convergence in Technology, I2CT 2024

作者： Tiwari, Abhishek Kumar, Santosh Mishra, Ashutosh Sehgal, Jiya Samita, Shammy Chandigarh University Computer Science & Engineering Mohali India

ISBN: (纸本)9798350394474

This research paper showcases a leading-edge Automatic Vehicle Number Plate Recognition (ANPR) system that capitalizes the potential of YOLOv8 (You Only Look Once) and Convolutional Neural Networks (CNN). The central objective of this system is to streamline the precise extraction of license plate information, with a prominent emphasis on precision, automation, and versatility. Moreover, it offers a rugged solution for thorough traffic monitoring and enforcement by integrating vehicle speed calculations. The combination of YOLOv8 and CNN significantly augments the image-processing capabilities of the system. To implement this ANPR system successfully, a series of critical steps have been followed, consisting of system setup, data collection, YOLOv8-based license plate detection with the help of CNN for licence plate character recognition, speed calculation through OpenCV, integration of components, rigorous testing, and finally, deployment. The fusion of these advanced technologies and methodologies, as elucidated in this paper, pledges to overhaul license plate recognition in the context of automated vehicle surveillance and traffic management. With an accuracy of 98.5% in the detection of number plates accompanied by an accuracy of 96% in speed recognition along with automation, and adaptability, this ANPR system holds tremendous potential for improving law enforcement, security, and transportation efficiency. © 2024 IEEE.

关键词： automation

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