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检索条件"任意字段=3rd International Conference on Robot Intelligence Technology and Applications"

共 6129 条记录，以下是291-300 订阅

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Enhanced Deep Dehazing for Haze Removal in License Plates 3

Enhanced Deep Dehazing for Haze Removal in License Plates

引用

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

作者： Suresh, Abishek Bharathi, R. Vijayakumar, Vaidehi SCOPE Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350372120

This paper introduces Enhanced Deep Dehazing (EDD), a novel deep learning model that overcomes the limitations of traditional image dehazing methods. Unlike approaches that rely on complex transmission map estimation, EDD utilizes an Encoder-Decoder architecture for direct data-driven learning. EDD effectively handles diverse hazy conditions that degrade image quality across various applications. It utilizes convolutional layers for feature extraction and deconvolutional layers for image reconstruction, employing ReLU activation and batch normalization to improve training stability and convergence. A case study on the application of EDD to car license plate dehazing, a critical task for autonomous vehicles and surveillance systems, is presented. EDD was trained and tested on the Foggy-Hazy Licence Plates dataset, with experimental results demonstrating superior efficiency compared to previous works, thus underscoring its effectiveness and potential in dehazing foggy/hazed license plates and highlighting its applicability in realworld scenarios. © 2024 IEEE.

关键词： Image reconstruction

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Water Quality Prediction and Suggesting Filter using Machine Learning 3

Water Quality Prediction and Suggesting Filter using Machine...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Chaudhari, Archana Mane, Rutuja Khot, Anant Kadam, Anup Rajam, Nagraj Department of Instrumentation Engineering Vishwakarma Institute of technology Bibwewadi Maharashtra Pune India

ISBN: (纸本)9798331527549

Survival of all living beings and efficient working of industries and agriculture are largely dependent on the availability of clean water. However, contamination is a major issue that requires dependable methods for assessing the quality of water before its use in drinking, chemical applications, or animal hydration. This research utilizes machine learning to predict water quality based on parameters such as pH, turbidity, hardness, conductivity, and dissolved particles. Based on a broad dataset, models such as time-series analysis and Random Forest classifier are applied to categorize water as safe or unsafe for domestic use. A hardware system equipped with sensors captures real-time data, which enables dynamic assessment of water quality. The proposed solution shows high accuracy in its evaluation using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Regression Analysis, offering a practical approach to ensure water safety in diverse applications. © 2025 IEEE.

关键词： artificial intelligence data visualization dataset filter hardware machine learning preprocessed data Random forest algorithm TDS water quality

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Unified Security Framework for Cloud applications with IoT Fusion via Decentralized Blockchain 3

Unified Security Framework for Cloud Applications with IoT F...

引用

3rd international conference on Applied Artificial intelligence and Computing, ICAAIC 2024

作者： Mohanraj, B. Kalpana A, M. Priya, M. Abdul Jaleel, D. Karthikeyan A, N. Velusamy, A. Sona College of Technology Department of Information Technology Salem India Government College of Engineering Department of Computer Science Engineering Salem India Knowledge Institute of Technology Department of Information Technology Salem India Madanapalle Institute of Technology & Science Department of Computer Science & Technology Madanapalle India Sri Venkateshwara College of Engineering Department of Cse - Artificial Intelligence Vidyanagar India

ISBN: (纸本)9798350375190

Recent advancements in blockchain-based cloud computing highlight its potential in providing robust data security, integrity, and confidentiality. While cloud computing is increasingly utilized for remote resource access, it presents significant security challenges that necessitate innovative solutions. This research proposes a novel SecureCloudChain IoT (SCC-IoT) architecture, which integrates blockchain technology into cloud-supportive platforms to enhance security measures. The SCC-IoT architecture includes a distributed blockchain approach to ensure data security while maintaining privacy and integrity. This system is designed to be adaptable and scalable, meeting real-world requirements effectively. By promoting a decentralized and efficient environment, SCC-IoT improves the reliability, stability, and load balancing of cloud services. Performance assessments through various experimental conditions have been conducted to evaluate the proposed system. The results demonstrate SCC-IoT's effectiveness in mitigating potential attacks and ensuring secure and reliable cloud computing. This research highlights the significance of integrating blockchain technology into cloud platforms, paving way for more secure and efficient cloud computing solutions. © 2024 IEEE.

关键词： Blockchain

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Navigating the Cloudscape: Framework and Strategies for Seamless Migration to the Cloud 3

Navigating the Cloudscape: Framework and Strategies for Seam...

引用

3rd international conference on Applied Artificial intelligence and Computing, ICAAIC 2024

作者： Kalpeshkumar, Patel Tirth Patel, Sachin Krimilkumar, Kalathiya Anilbhai, Bhalani Deep Patel, Ankur Nayak, Amit Devang Patel Institute of Advance Technology and Research Charotar University of Science and Technology Changa India Chandubhai S. Patel Institute of Technology Charotar University of Science and Technology Changa India

ISBN: (纸本)9798350375190

Enhancing agility, scalability, and cost-efficiency in IT infrastructure are some of the key objectives that push companies to consider cloud migration as a crucial strategy. This article gives an introduction about cloud migration illustrating why it is significant, difficulties experienced and its advantages. The method of moving on-premises applications, data, and infrastructure to cloud-based environments involves more preparation, evaluation and implementation to achieve seamless transition while minimizing disruptions to business operations. These must include choosing among the three main categories of service delivery models: Platform as a Service (PaaS), Software as a Service (SaaS), and Infrastructure as a Service (IaaS). Selecting the best provider for cloud computing services for a business deal with security issues compliantly and achieve optimization of different performance levels at minimum costs. This process has its share of challenges such as data migration complexities, application compatibility issues and organizational resistance towards change. In spite of this, there are ways that can be followed to unlock the full potential in cloud computing so that innovation, agility and competitive advantage may be realized in today's digital world. © 2024 IEEE.

关键词： Competition

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3rd international conference on Mechanical and Energy Technologies, ICMET 2023

3rd International Conference on Mechanical and Energy Techno...

引用

3rd international conference on Mechanical and Energy Technologies, ICMET 2023

ISBN: (纸本)9789819727155

The proceedings contain 50 papers. The special focus in this conference is on Mechanical and Energy Technologies. The topics include: A Numerical Investigation on Estimation and Validation of Power Law Constants for TiB2 Reinforced AA2024 Composite Material;Power Flow Control of the Grid-Integrated DG System Using Hybrid Aquila Optimizer‑Tangent Search Algorithm;Design and Analysis of Manual Pallet Stacker by Using FEM Method;Design and Development of an IoT Counter Using ESP8266 for 6 Axis MIG Welding robot;In-Depth Examination of the Mechanical Properties of AA6061/MoS2/SiC Hybrid Composites;optimization of Microchannel Heat Sink Shapes to Enhancing Electronic Cooling Efficiency;empowering Next-Generation Energy Infrastructure Through IoT for Climate Resilience;safeguarding Cryptocurrency Transactions: Leveraging Blockchain and Machine Learning for Enhanced Financial Security;utilizing Machine Learning for Advanced Natural Language Processing and Sentiment Analysis in Social Media Platforms;improving Image Clarity with Artificial intelligence-Powered Super-Resolution Methods;revolutionising Tumour Diagnosis: How Clinical Application of Artificial intelligence and Machine Learning Enhances Accuracy and Efficiency;harnessing Medical Databases and Data Mining in the Big Data Era: Advancements and applications in Healthcare;machine Learning-Powered Design and Implementation for Classification of Missing Data in IoT applications;ioT-Based Security Detection for Cloud Web applications: Leveraging Internet of Things Approaches;Exploring Ethical Considerations: Privacy and Accountability in Conversational Agents like ChatGPT;navigating Cross-Lingual Natural Language Processing: Challenges, Strategies, and applications;fostering Understanding: Bridging the Gap Between Black-Box Models and Human Interpretability with Explainable Artificial intelligence;semantic Analysis and Machine Learning Techniques for Enhancing Content-Based Image Retrieval.

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3rd international conference on Mechanical and Energy Technologies, ICMET 2023

3rd International Conference on Mechanical and Energy Techno...

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3rd international conference on Mechanical and Energy Technologies, ICMET 2023

ISBN: (纸本)9789819749461

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Big Data Analysis and applications in international Trade: Decision Optimization Based on Intelligent Algorithms 3

Big Data Analysis and Applications in International Trade: D...

引用

3rd IEEE World conference on Applied intelligence and Computing, AIC 2024

作者： Yang, Wenwen Jiangxi College of Foreign Studies Nanchang330096 China

ISBN: (纸本)9798350384598

In the field of international trade, due to its wide range and complex interest relations, it is necessary to synthesize various information for analysis and decision-making. However, traditional data processing methods have been unable to meet the needs of enterprise development. As a new, efficient, safe and reliable solution, large database technology has been widely used in various fields and achieved good results. The purpose of this paper is to discuss and study the cross-department collaboration problem driven by intelligent algorithm through application examples. This paper first introduces the basic concepts, characteristics and relevant theoretical basis of inter-departmental collaboration. By studying the application of intelligent algorithms in interdepartmental collaboration, effective decision support tools are provided to deal with the complex situations in international trade. After that, this paper conducts a simulation test on the intelligent algorithm-driven decision optimization model, and the test results show that the test range of this model for the risk-return rate in trade is 0.04-0.09. © 2024 IEEE.

关键词： big data analysis decision optimization intelligent algorithms international trade

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Bibliometric Analysis of Application of Artificial intelligence in Heart Disease: 2013 to 2023 3

Bibliometric Analysis of Application of Artificial Intellige...

引用

3rd IEEE international conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Roy, Ankita Garg, Atul Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350343274

The use of cutting-edge technologies in healthcare evolves continuously. Artificial intelligence offers a wide range of applications in the diagnosis, detection, or early prediction of many diseases. This research work was conducted to outline the current research directions in the area of artificial intelligence applications for cardiac disease. The various bibliometric analysis approaches are used between 2013 and 2023 to evaluate the potential for research in the field of applications of artificial intelligence in heart disease. Initially, search strategy 1 was used to retrieve 1128845 papers, while search strategy 2 was used to retrieve 581739 papers. Finally, the AND operator was used to combine search strategies 1 and 2 to include 50196 publications that perfectly matched our objectives. This research work found that: (1) The number of publications in the field of application of Artificial intelligence in Heart Disease increased exponentially;(2) there is 33440 groups or organisation involved out of it 242 has at least 5 research publications;(3) There is 16187 keywords available with this research topic. © 2023 IEEE.

关键词： Diseases

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Role of Artificial intelligence and Machine Learning in scalable Internet of Things applications 3

Role of Artificial Intelligence and Machine Learning in scal...

引用

3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Singla, Neeraj Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350330724

Anything non-living that can take decisions on its own is called artificially intelligent. It is a technique designed to mimic human behaviour. On the other hand machine learning if a subset of artificial intelligence. It is a statistic method used to enable machine to improve with experience. They both go hand in hand. Now IoT has been there in existence for an enormous amount of time but during recent times due to large scale good connectivity for efficient data transfer, Machine learning and analytics and Conversional Artificial intelligence has made IoT possible. © 2023 IEEE.

关键词： Internet of things

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Alzheimer's Disease Diagnosis Using Artificial intelligence and MRI Images of the Brain 3

Alzheimer's Disease Diagnosis Using Artificial Intelligence ...

引用

3rd international conference for Innovation in technology, INOCON 2024

作者： Das, Tulip Nayak, Chinmaya Kumar Pattnayak, Parthasarathi Sri Sri University Faculty of Emerging Technologies Cuttack India Kiit Deemed to Be University School of Computer Applications Bhubaneswar India

ISBN: (纸本)9798350381931

One major neurodegenerative disease that primarily affects the senior citizen and pre-elderly population is Alzheimer's disease. Advances in AI-enhanced detection for Alzheimer's disease have been spurred by recent developments in MRI technology, raising hopes for early detection and prompt therapies. This advancement has made it possible to create complicated models and algorithms that can analyse imaging data, improving the efficiency and accuracy of diagnosis. It gives rise to hope for the groundbreaking possibilities in transforming the management of Alzheimer's disease and more successful treatment plans and better patient outcomes. This article aims to give a thorough overview of current advancements in DL techniques used to classify different stages of Alzheimer's disease based on brain MRI scans, with a focus on early diagnosis. It also discusses possible obstacles and future research possibilities, highlighting the shortcomings of the current research. © 2024 IEEE.

关键词： Neurodegenerative diseases

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