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共 6998 条记录，以下是191-200 订阅

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Deep Learning-Based Image Analysis for Detecting Nutrient Deficiencies of Tomato Plants 5

Deep Learning-Based Image Analysis for Detecting Nutrient De...

引用

5th International Conference on Advancements in Computing, ICAC 2023

作者： Nirasha Jayasiri, K.C. Chandrasiri, Sanjeevi Rupasinghe, Shalini Karunanayake, K.O. Rivindu Uthayachandran, Abineshh Zihara, M.I. Fathima Sri Lanka Institute of Information Technology Dept. of Computer Science and Software Engineering Sri Lanka

ISBN: (纸本)9798350358131

Tomato is one of the most popular crops worldwide. The success of a tomato crop is highly dependent on the health of the plants. Nutrient deficiency surveillance is typically conducted through visual inspections, which can be challenging for inexperienced farmers and home gardeners to work accurately. There is a growing need for a quick, reliable, and accurate nutrient deficiency identification system to address this issue. The proposed method is based on image processing and deep learning technologies that are highly effective for image classification tasks. Two models were trained using a dataset collected from tomato plants in Sri Lanka and evaluated using Mask Region-based Convolutional Neural Network (Mask R-CNN) and, You Only Look Once (YOLO) for deficiency classification, and results obtained 92% and 98% accuracy, respectively. Deficiency dispersion level expressed as a percentage using Mask R-CNN and followed by image processing techniques. Overall, this proposed system offers a convenient and accessible tool for farmers and home gardeners to monitor and maintain the health of their tomato plants, enabling them to achieve optimal yields and ensure profitable returns. © 2023 IEEE.

关键词： Object detection

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Design of QR Code Tracking Car based on Monocular Vision

Design of QR Code Tracking Car based on Monocular Vision

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Shen, RuiBing Chang, Chih-Yung Hu, ZhiJie Wu, Shih-Jung Hou, Di Xi'an Eurasia University School of Information Engineering Xi'an China Dept. of Computer Science and Information Engineering Tamkang University Taiwan Xi'an ShiYou University Dept. of Electronic Engineering China

ISBN: (纸本)9798350324174

This paper designs an automatic tracking car that uses machine vision technology to realize QR code recognition. The car uses the MSP430F5529 chip as the main controller. It uses the OpenMV camera as the image acquisition sensor and the OpenCV library to process the acquired images. It can locate the target of the QR code by monoculture visual positioning technology. The car can obtain the distance between it and the leading vehicle, and compare the actual distance with the expected distance. The main controller can control the motor operation according to the distance deviation obtained, aiming to realize the automatic following function of the car. © 2023 IEEE.

关键词： Controllers

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Foreign Exchange Market Analysis based on Novel Grey Wolf based Extreme Learning Machine Predictor 4

Foreign Exchange Market Analysis based on Novel Grey Wolf ba...

引用

4th International Conference on Emerging Systems and Intelligent Computing, ESIC 2024

作者： Dash, Swaty Sahu, Pradip Kumar Mishra, Debahuti Veer Surendra Sai University of Technology Burla Dept. of Information Technology Odisha Sambalpur India University Dept. of Computer Science & Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798350349856

Foreign exchange trading basically bridges a gap between buyer and seller to transact at a set of prices of the currencies to make profit out of it by the traders and investors. In this paper, foreign exchange predictive models are explored based on basic Extreme Learning Machine (ELM) along with optimized version of ELM. Initially, this work tried to obtain the best optimized ELM network based upon the four nature-inspired optimization methodologies such as;particle swarm, ant colony, moth flame and grey wolf optimization (GWO). From this phase, it has been observed that the ELM network optimized with GWO outperforms rest of other experimented optimized ELM networks with respect to error graphs and performance metrics. In order to evaluate the performance, the ELM-GWO currency exchange predictor, the recognition performance metrics such as;EVS, MAE, MSE and R2 Score are computed, the error graphs are obtained and the average computational time taken are compared. © 2024 IEEE.

关键词： Ant colony optimization

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Analyzing Voice Quality with Multi-Dimensional Voice Program for Disease Determination 6

Analyzing Voice Quality with Multi-Dimensional Voice Program...

引用

6th International Symposium on computer, Consumer and Control, IS3C 2023

作者： Liza, Rahmi Tsung, Chen-Kun National Chin-Yi University of Technology dept. Computer Science and Information Engineering Taichung Taiwan

ISBN: (纸本)9798350301953

Multi-Dimensional Voice Program (MDVP) parameters are very popular among physicians/clinicians to detect vocal pathologies and analyze various diseases of the vocal cords. In this paper, voice pathologies are automatically detected using the parameters of the MDVP. However, MDVP is commercial software, so this work is trying to build MDVP using Python to extract MDVP parameters useful for various experiments, automatic detection of sound pathologies, and automatic classification of voice recognition. This study evaluates MDVP parameters and applies the XGBoost model as a classification method to analyze and classify diseases. This work considers three sample data, polyps, nodules, and Reinke edema, popular in clinical vocal cords diseases, from Saarbruecken Voice Database (SVD) for data testing and training. Test results demonstrate the excellent ability of MDVP's parameter extraction to identify healthy voices and obtain accurate classification results to discriminate between healthy voices and pathological voices. The best overall accuracy is 98% using the XGBoost classifier. © 2023 IEEE.

关键词： Classification (of information)

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An Effective Prediction of Rainfall Using Machine Learning Technique 5

An Effective Prediction of Rainfall Using Machine Learning T...

引用

5th IEEE International Conference on Electrical, computer and Communication Technologies, ICECCT 2023

作者： Rana, Nisha Guru Prasad, M. Sharma, Ashutosh Pratap, M.S. Anand Kumar, M. Aditya Pai, H. Dept. of Computer Science and Engineering Rishikesh India Graphic Era Deemed University Dept. Computer Science and Engineering Dehradun India Rishikesh India School of Computing and Information Technology Reva University Bengaluru India Dept. of Computer Application Dehradun India Dept. of Computer Science and Engg. Dehradun India

ISBN: (纸本)9781665493604

Climatic information such as temperature, humidity, and precipitation are useful for agriculturists, businesses, researchers, and the government. Estimating precipitation is a major factor that affects the environment and is one of the most important aspects of meteorological science. In this study, factual approaches and machine learning methods are used to estimate and forecast meteorological parameters for the government. Estimating precipitation is a major factor that affects the environment and is one of the most important aspects of meteorological science. Approaches are used to forecast and estimate precipitation. Daily observations were used as part of the experiment. Validation of results using real-world data is used to check the accuracy of forecasting model experimentation. The experimental results show that distribution, correlation, line-plots, and neural networks perform well for forecasting meteorological characteristics and have the best classification accuracy when compared to other types of machine learning methods for precipitation forecasting. © 2023 IEEE.

关键词： Machine learning

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Instance Segmentation based Object Detection with Enhanced Path Aggregation Network

Instance Segmentation based Object Detection with Enhanced P...

引用

2023 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2023

作者： Onthoni, Ade Indra Sahoo, Prasan Kumar Dept. of Computer Science and Information Engineering Chang Gung University Guishan Taoyuan33302 Taiwan

ISBN: (纸本)9798350348071

Multi-scale networks rely heavily on the aggregation process to aggregate feature information into other feature maps. However, it has disadvantages in aggregating information, where the localization information becomes inconsistent. An Enhancing Path Aggregation Network through concatenation and attention mechanism is proposed here to improve the aggregation path for generating the feature maps in multi-scale network. This approach helps to keep information consistently during the process of aggregation. The proposed model is evaluated using the COCO dataset, which achieves significant improvements on several metrics. © 2023 IEEE.

关键词： Object detection

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Multicarrier Waveforms for Moon-to-Earth RF Transmission 10

Multicarrier Waveforms for Moon-to-Earth RF Transmission

引用

10th IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2023

作者： Rahman, Talha Faizur Marojevic, Vuk Sacchi, Claudio Mississippi State University Dept. of Electrical and Computer Engineering Mississippi StateMS United States University of Trento Dept. of Information Engineering and Computer Science Trento Italy

ISBN: (纸本)9781665456906

More than 50 years after the last Apollo mission, the race to the Moon has started again. In the framework of new missions, it will be of paramount importance to establish a reliable communication link between the vehicles (or astronauts) present on the Moon's surface and an Earth station. Alternative choices consider radio-frequency (RF), optical, and hybrid optical-RF solutions. In this paper, we focus on the RF transmission case. Recent works evidenced how diversity is required to face multipath fading issues due to the reflection of electromagnetic rays on the Lunar surface. For this reason, suitable waveforms, which are robust against multi path distortion should be considered. In this work, we propose multicarrier Orthogonal Frequency Division Multiplexing (OFDM), Single-Carrier OFDM (SC-OFDM), and Constant-Envelope OFDM (CE-OFDM). The comparative results will be discussed in order to select the best solution to cope with the various tradeoffs between link performance, spectral efficiency, and computational complexity. © 2023 IEEE.

关键词： 5G mobile communication systems

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Unlocking Efficiency in Agricultural Supply Chains: A Secure and Transparent Approach through Blockchain Technology

Unlocking Efficiency in Agricultural Supply Chains: A Secure...

引用

2024 IEEE International Conference on Emerging Technologies in computer science for Interdisciplinary Applications, ICETCS 2024

作者： Lohith, J.J. Shreya, S. Hamsa Priya, J.L. B.M.S. College of Engineering Dept. of Computer Science and Engineering Bangalore India D.S.C.E Dept. of Information Science and Engineering Bangalore India B.M.S. College of Engineering Dept. of Electronics and Telecommunications Bangalore India

ISBN: (纸本)9798350372502

Supply Chain Management (SCM) involves orchestrating various processes that extend from acquiring raw materials to delivering finished products to end consumers. The key objectives of a proposed supply chain in agriculture, emphasizes information-driven processes, cost reduction, and customer impact. It creates a versatile system capable of managing the supply chain for diverse commodities within a country, while also addressing the crucial need for increased transparency and traceability in data throughout the chain of activities. In our proposed approach to agricultural supply chain management (SCM), the focus is on creating a secure, transparent, and traceable SCM. To achieve this, we leverage cutting-edge technologies like the Ethereum blockchain and the Interplanetary File System (IPFS). The resulting software is a Decentralized Application (DApp) that orchestrates a series of activities within the agricultural industry, using cryptocurrencies to establish a seamless and efficient supply chain management system. This software platform is fortified by the secure algorithms of blockchain, providing an added layer of reliability. Additionally, our application incorporates transparency and traceability, ensuring user-friendly functionality and making it more accessible for users. © 2024 IEEE.

关键词： Blockchain

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Design and Implementation of the Crib Monitoring System

Design and Implementation of the Crib Monitoring System

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Hu, ZhiJie Chang, Chih-Yung Shen, RuiBing Wu, Shih-Jung Hou, Di Xi'an Eurasia University School of Information Engineering Xi'an China Tamkang University Dept. of Computer Science and Information Engineering Taiwan Xi'an ShiYou University Dept. of Electronic Engineering China

ISBN: (纸本)9798350324174

This paper designs a crib monitoring system based on the STM32 microcontroller. The system uses temperature and humidity sensors to collect the ambient temperature and humidity. The microcontroller processes and analyzes the collected data, and displays it through the display module. When the temperature is higher or lower than the preset threshold, the fan module or heating module is started to adjust the temperature. The temperature threshold is set by the key module. The system will give an alarm when the baby touches the fence to prevent the baby from falling. The system can adjust the motor speed through the key module, aiming to control the crib swing speed. Lullabies are played through the voice broadcasting module to help the baby relax and fall asleep;In addition, the temperature and humidity information is uploaded to the mobile terminal for real-time display through the Bluetooth communication module, and the mobile terminal can also control the motor speed, playing, and music switching. The test result shows that the crib monitoring system has the characteristics of fast response speed, high identification accuracy, and good stability. It can provide a theoretical basis for the actual crib production, and has a certain reference value. © 2023 IEEE.

关键词： Microcontrollers

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Multi-agent Task Assignment in Unmanned Aerial Vehicle Edge Computing based on Deep Learning Approach 3

Multi-agent Task Assignment in Unmanned Aerial Vehicle Edge ...

引用

3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Samuel, Amalorpava Mary Rajee Yamuna Devi, M.M. Madhusudhanan, S. Dept. of Electrical and Information Engineering University of Witwatersrand Johannesburg South Africa Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundatio Vijayawada India Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9798331532420

Unmanned aerial vehicles (UAVs) are used as supportive edge computing for sparsely located user equipment on a large scale. In this work, we propose and address a collaborative edge computing system involving multiple UAVs as agents in deep reinforcement learning (DRL) approach due to the restricted computation and energy capabilities of UAVs. The challenge of task offloading is being tackled to reduce the total delays in execution and energy usage by simultaneously planning the paths, assigning computation tasks, and managing communication resources of UAVs. Additionally, Lyapunov optimization is incorporated for the system stability of mobile edge computing assisted by multiple UAVs. Exploring a multi-agent deep reinforcement learning framework to achieve a combined strategy to manage task allocation, and power management. The sum rate results of the evaluation show that our method for task offloading using multi-UAV and multi-EC achieves superior performance with 25 % increase when compared to other optimization methods and ability to reduce cost and delay. © 2024 IEEE.

关键词： Energy utilization

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