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YOLO Dietician 3

YOLO Dietician

引用

3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Vaishnavi, Sirikonda Shetty, Sanne Hruthika Maheswari, M. Jany Shabu, J.L. Refonaa, J. Sathyabama Institute of Science and Technology Department of Cse Chennai India Sathyabama Institute of Science and Technology Dept.of Computer Science and Engineering India

ISBN: (纸本)9798350375190

In recent years, the integration of Artificial Intelligence (AI) in healthcare has attracted a lot of attention, particularly in the domain of personalized nutrition. With the rising prevalence of diet-related health issues such as obesity, diabetes, and cardiovascular diseases, the primary objective of this research study is to design and implement a platform capable of analyzing individual preferences, nutritional needs, health goals, and lifestyle factors to offer customized dietary guidance and management. This research study proposes a AI Dietician by utilizing AI algorithms to provide personalized dietary recommendations. This study also covers the technical aspects and methods used in creating a AI dietician, including feature extraction, algorithm selection, data gathering strategies, and model training by ultimately contributing to the prevention of diet-related health issues and promoting long-term health outcomes. © 2024 IEEE.

关键词： Nutrition

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Non-Invasive Oral Cancer Detection Using Hyperspectral Imaging and Advanced Spectral Unmixing Models

Non-Invasive Oral Cancer Detection Using Hyperspectral Imagi...

引用

2024 IEEE International Conference on Intelligent Computing and Emerging Communication Technologies, ICEC 2024

作者： Ayyapa, Valluri Kothamasu, Kesava Sriram Killaru, Priyusha Muddana, Saadhivik Aala, Suresh Gutha, Vamsi Kumar, Mukkara Prasana Chinnadurai, Sunil SRM University Dept.of Electronics and Communication Engineering AP India SRM University Dept. of Computer Science and Engineering AP India SRM University Dept. of Computer Science AP India

ISBN: (纸本)9798331508432

Oral cancer is a significant global health concern, often leading to high mortality rates due to late-stage diagnosis and the lack of effective early detection methods. Despite advances in medical science, the absence of reliable early diagnostic tools remains a critical challenge. Hyperspectral imaging (HSI) has emerged as a powerful noninvasive technology, capturing detailed spectral information across a wide range of wavelengths. This allows for accurate differentiation between cancerous and healthy tissues, improving early detection and enhancing treatment outcomes. In this study, we propose the use of HSI for early oral cancer diagnosis. To address the scarcity of labeled data, we developed a synthetic hyperspectral dataset that includes spectral signatures of both normal and cancerous tissues. The dataset was generated using a bilinear mixing model, with key spectral features extracted through Vertex Component Analysis (VCA) and abundances computed using Non-Negative Least Squares (NNLS). The model's performance was evaluated using Spectral angle distance (SAD) and Root mean square error (RMSE) metrics. Our findings demonstrate that HSI significantly improves the accuracy of early oral cancer detection, outperforming traditional methods. This work highlights the potential of advanced imaging technologies in revolutionizing cancer diagnosis, offering a robust framework for non-invasive detection and showcasing the effectiveness of synthetic datasets in medical imaging research. © 2024 IEEE.

关键词： Deep Learning Hyperspectral Imaging (HSI) Non-Negative Least Squares (NNLS) Oral Cancer Detection Root Mean Square Error (RMSE) Spectral Angle Distance (SAD) Synthetic Dataset Vertex Component Analysis (VCA)

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A Solid Waste Management System Using Smart Bins in a Decentralized Manner in Ethereum Blockchain Network for Incentivization 2

A Solid Waste Management System Using Smart Bins in a Decent...

引用

2nd International Conference on Computational Systems and Communication, ICCSC 2023

作者： Amitha, A.K. Pamba, Raja Varma LBS Institute of Technology for Women Dept.of Computer Science and Engineering Thiruvananthapuram India

ISBN: (纸本)9781665493932

Waste generation in the world is raising in a huge way that the requirement to devise new solutions is crucial. The Solid Waste Management, SWM finds it difficult to handle manually these waste generated day by day, as a result of urbanization. With the advent of the technologies, it is possible to find some really good solutions for the waste segregation, waste collection, tracking, and documenting on the entire process. In this paper, we propose an automated solid waste management system by bringing the IoT and block chain technologies together. Here the data related to the bin is collected and is passed to the blockchain smart contracts that can automate incentives. The system enables waste segregation, which will ease the further procedures in SWM. Smart contract is deployed in the public blockchain Ethereum network platform and the automated reward based on the weight and type of the waste through an API is proposed in this paper. © 2023 IEEE.

关键词： Ethereum

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A Machine Learning and Deep Learning Based Approach to Detect Inaccurate Health Information in Bengali Language 3

A Machine Learning and Deep Learning Based Approach to Detec...

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3rd International Conference on Electrical, computer and Communication engineering, ECCE 2023

作者： Taki, Nusrat Showan, Eshatur Chowdhury, Umratul Tasnim, Farzana International Islamic University Chittagong Dept.of Computer Science and Engineering Chittagong4318 Bangladesh

ISBN: (纸本)9798350345360

The spread of false health news and its dis-semination on the internet has become a major concern, due to its potential to have disastrous effects. To detect it, numerous approaches have been attempted. However, we are aware of very few studies that have sought to identify health related false information in Bangla. In this study, we have analyzed the performance of various Machine Learning and Deep Learning approaches in detecting Bangla health-related misinformation that is available online. We have created a comprehensive data repository, consisting more than 5000 data, manually annotated to two fixed categories. Several supervised machine learning classifiers and Deep Learning algorithms have been employed in this experiment to detect fake health news at the textual level. Our experiment achieves maximum accuracy of 88% in the Passive Aggressive approach and 89% in the Bi-LSTM approach. We believe that our dataset is a significant collection of health-related data in Bangla. It may open up new perspectives for the analysis of Bangla-language and health misinformation detection. © 2023 IEEE.

关键词： Long short-term memory

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Text Transmission Through Li-Fi in WSN Using Smart Based Secure Morse Code Algorithm

Text Transmission Through Li-Fi in WSN Using Smart Based Sec...

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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Vasudevan, I. Malathi, P. Siddik, S. Therasa, P.R. Nasurudeen, M.Mohamed Charaan, R.M.Dilip Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Dept.of Cse Chennai India Saveetha College of Liberal Arts and Sciences Simats Dept of Computer Science India Pavaai Engineering College Dept.of Eee Namakkal India R.M.K Engineering College Dept.of Cse Kavaraipettai India V.S.B Engineering College Dept.of Cse Karur India

ISBN: (纸本)9798331509828

Cyber security is one the most challenging task in today's world. Most of the existing Li-Fi technology in wireless sensor network is to detect the data within the short range of distance less accuracy. In this research, we proposed a Smart based Secure Morse Code (SSMC) technique. Here there are two part, first is encoding and next is decoding. This proposed encoding technique takes user input in text based form and convert these text to standard morse code pattern and decoding does in the opposite direction. The transmitter parts encode the user input and send the pattern through laser module. The receiver part receives the pattern sends to microcontroller and then decodes and displays the data. In our experiment results shows that the proposed technique can transmit data over long distance with help of morse code encoding decoding algorithm. This technique takes 5ms for the whole transmission and process the transmission accurately. © 2025 IEEE.

关键词： Encoding (symbols)

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Continuous Tweet Stream Analysis using Apache Spark Streaming API & Kafka 15

Continuous Tweet Stream Analysis using Apache Spark Streamin...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Nisha, A.G. Shivaprasad, N. Nischitha, C.B. Shashikala, B.M. Sujithra, M. Chaba, Yogesh Electronics & Communications Engineering JSS Science & Technology University Mysuru India Dept.of Electronics & Communications Engineering Sri Jayachamarajendra College of Engineering JSS Science & Technology University Mysuru India Dept.of Computer Science St.Joseph's First Grade College Mysore India Dept.of Computer Applications Sri Jayachamarajendra College of Engineering JSS Science & Technology University Mysuru India Department of Computing-Data Science Coimbatore Institute of Technology Coimbatore India Department of Computer Science and Engineering Guru Jambeshwar University of Science and Technology Haryana Hisar India

ISBN: (纸本)9798331300579

Social media has become a trend nowadays people are spending more time in social media platform like Facebook, Twitter, Instagram to share their opinions, creating new interests, ideas and generate *** provide a major platform for collecting information which helps us to analyze them for our *** such microblogging social network is twitter which allows information collaboration and quick information sharing that provides relief from rising *** has several millions of people tweeting and expressing their perspectives on a due to its distinctively brief and straightforward expressing *** enormous volume of raw data from tweets can be utilised for analysis and processing based on industrial or business *** this technical paper, the application of tweet sentiment analysis by extracting a vast number of tweets using continuous tweet stream provided by Spark and Kafka has been *** system fetches live tweets from Twitter based on the search criteria, process the tweets, by using text mining techniques and classify them based on different labels. © Grenze Scientific Society, 2024.

关键词： Tweets

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Human Activity Recognition using ShuffleNetV2 Model

Human Activity Recognition using ShuffleNetV2 Model

引用

2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Shanufa Nazrin, P.S. Benifa, J.V. Bibal Anu, K.P. Vijayakumar, Aiswarya Dept. of Computer Science Kerala Thrissur India Indian Institute of Information Technology Dept.of Computer Science and Engineering Kerala kottayam India

ISBN: (纸本)9798350394580

HAR is specified as the crucial task within the field of computer vision and artificial intelligence. Main aim of HAR is to observing and labelling different human activity images of distinct data sources by machines such as computer. HAR has applications in various fields. CNN model is an appropriate model for HAR task, due to their ability to automaticaly acquire relevant spatial features, capture hierarchical representations, and handle input of various sizes and types. So it is utilized for developing HAR model. This model can detect objects and also can classify images. The model contains wide ranging catogories. ShuffleNetV2 is a particular architecture within it, mainly for efficient and lightweight deep learning task. This paper develops an intelligent HAR using ShuffleNetV2 model which acquired an accuracy about 69.52 percentage. © 2023 IEEE.

关键词： HAR Human activity ShuffleNetV2

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Augmented Reality based WayFinder System in Libraries 2

Augmented Reality based WayFinder System in Libraries

引用

2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Aiswarya, R. Sreeram, V.K. Anchana Jinesh, K. Sneha, V.P. Menon, Hema P. Dept.of Computer Science and Engineering Sreepathy Institute of Mnagement and Technology Vavanoor Kerala Palakkad India

ISBN: (纸本)9798350340235

Advancement in technology can be utilized to ease workloads in many scenarios. In libraries, the search for a particular book may take a lot of time, and memorizing the position of each book is not an easy task and may result in reducing a person's interest in visiting the library. Usage of Augmented Reality, helps in visualizing the plots of the library. After combining with GPS, the system will be able to suggest the path to desired book in minimum required time. In libraries, there can be multiple paths to reach a particular book. The proposed system compares the multiple paths to find the best way with minimum distance to reach the desired book. The developed Augmented Reality wayfinding system revolutionizes the library experience by overlaying directional information or real environments through a smartphone camera. Scanning a provided QR code in the library helps the users to access the interface of the system and search for the required book. Innovation of such a system not only simplifies the search for books but also enables customers to check book availability and stock levels via a database. It also suggests alternatives, if the specific book is unavailable. By engaging such on-screen bots overall user experience can be enhanced and workload can be minimalized. © 2023 IEEE.

关键词： Augmented Reality (AR) Global Positioning System (GPS) Navigation Unity

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Advancements in Flood Mapping Methodologies: A Comprehensive Review 6

Advancements in Flood Mapping Methodologies: A Comprehensive...

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6th IEEE International Conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Chandran, Divya V Anitha, J. Chandran, Divya V Vijayakumar, Amrutha Raveendran, Anjana Karunya Institute of Technology and Sciences Dept.of Computer Science Engineering Coimbatore India Adi Shankara Institute of Engineering and Technology Dept. of Electronics and Communication Engineering Kalady India

ISBN: (纸本)9798350381689

This review aims to comprehensively assess the recent advancements in flood mapping methodologies and technologies. By analyzing diverse techniques and approaches employed in flood mapping, this review seeks to present an in-depth overview of the current landscape of this field. The primary focus is on evaluating the strengths and limitations inherent in various flood mapping methods. Special attention will be given to exploring the integration of remote sensing technologies and geographic information systems (GIS) in flood mapping. Additionally, the review will delve into the transformative impact of machine learning and artificial intelligence on enhancing the precision and efficiency of flood mapping processes. Recent developments in flood mapping have significantly elevated the accuracy and reliability of the techniques employed. The integration of AI technologies with remote sensing methods has notably contributed to this advancement. Conventional approaches to flood mapping have traditionally relied on multiple methodologies to comprehend potential flood impacts. However, these methods often prove laborious, resource-intensive, and may lack access to real-time data, posing limitations for precise flood mapping and prediction. These identified limitations underscore the critical need for the development of more robust flood mapping techniques. Addressing these challenges is essential for enhancing flood risk assessment, improving management strategies, and ensuring better preparedness for future flood events. © 2024 IEEE.

关键词： Floods

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Smart Commerce: Unleashing Machine Learning for Optimal Customer Experiences

Smart Commerce: Unleashing Machine Learning for Optimal Cust...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Agarwal, Rachna Agarwal, Shipra Mittal, Varsha Graphic Era Deemed to be University Dept.of Commerce Dehradun India Graphic Era Deemed to be University Dept of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350378092

Machine learning is a branch of Artificial Intelligence (AI) and computer technology which address on the usage or application of data and Algorithms to emulate the style that humans learn, gradually improving its accuracy. By understanding this statement humans are not associated with machine learning, once the system is deployed by them. Once the whole system is installed in the software through algorithm or coding, the machine adapts the order and continues accordingly without hindering little things like Sleeping, fatigue like humans and can work for long time and can operate it 24/7, with repetition. But the system must be kept up-to-date. E-commerce or electronic commerce is the trading of goods and services, or transmitting of funds or data, over an electronic network, primarily in internet. In this paper, we will explore the crucial role that machine learning plays in the e-commerce sector, highlighting its impact on various aspects of digital commerce and its importance for organizations in the contemporary business landscape. © 2024 IEEE.

关键词： Adversarial machine learning

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