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Deep Learning based Driver Drowsiness Detection in Real Time Environment - An Enhanced Approach 4

Deep Learning Based Driver Drowsiness Detection in Real Time...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Ajay, Ashin Ashok, Naveen Kumar balajiram, Gokul Tamizhselvan, Abinesh Thangavel, Senthil Kumar Somasundaram, K. Amrita Vishwa Vidyapeetham M. Tech in Artificial Intelligence Coimbatore India Amrita Vishwa Vidyapeetham B. Tech in Computer Science and Engineering Coimbatore India Amrita School of Computing Coimbatore Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India School of Physical Sciences Department of Mathematics Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9798331523923

Effective driver behavior monitoring is necessary due to the increase in traffic accidents caused by distracted driving. In order to identify distractions such as talking, drinking, napping, and using a phone, this research suggests a CNN-based methodology. The model uses facial characteristics such as eyes to detect and analyze these activities. Thousands of photos depicting various distracted driving postures are used to train it on a publicly accessible dataset. The strategy seeks to improve road safety by offering a reliable way to identify distractions. © 2025 IEEE.

关键词： Convolutional neural networks

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Deep Learning for Glioblastoma Subtyping: Leveraging DenseNet-201 in brain Tumor Radiogenomic Classification 1

Deep Learning for Glioblastoma Subtyping: Leveraging DenseNe...

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1st IEEE International Conference on Cognitive Robotics and Intelligent Systems, ICC - RObINS 2024

作者： Jesuraj, S. Alvin Evangelin Sonia, S.V. Shirley, C.P. Karunya Institute of Technology and Sciences B.Tech Computer Science and Engineering Tamil Nadu Coimbatore India Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore India

ISBN: (纸本)9798350372748

This research investigates the application of DenseNet-201, a deep convolutional neural network architecture, in the RSNA-MICCAI brain Tumor Radiogenomic Classification aimed at predicting the genetic subtype of glioblastoma using MRI imaging data. This study demonstrates the effectiveness of DenseNet-201 in accurately classifying glioblastoma cases based on MGMT promoter methylation status, a critical biomarker influencing treatment outcomes. Through comprehensive experimental evaluations, including training, validation, and testing phases, DenseNet-201 exhibits robust performance metrics such as high accuracy, precision, recall, F1-score, and AUC-ROC values. These results highlight the model's ability to effectively distinguish between MGMT promoter methylation-positive and negative glioblastoma cases, offering valuable support for clinical decision-making in treatment planning and prognosis assessment. Leveraging deep learning techniques and MRI imaging data, DenseNet-201 holds promise as a powerful tool for enhancing the understanding of glioblastoma genetics and guiding personalized therapeutic interventions, ultimately contributing to improved patient outcomes in brain cancer management. © 2024 IEEE.

关键词： biomarkers

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Multilingual Contemplation for Social Media data by Hybrid Classifier

Multilingual Contemplation for Social Media data by Hybrid C...

引用

2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022

作者： Manoj, Challapalli Tejaswi, Talluru Sohana Nekkanti, Devi Sai Valiveti, Sriram Ganesan, Vithya Ramasamy, Viswanathan B. Tech Koneru Lakshmaiah Education Foundation Computer Science and Engineering Guntur India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

Sentiment analysis procure substantial contemplation for abandon growth of the web and social media. The goal is to identify opinions, sensation, or conviction of multilingual tweet. A large set of manually labeled tweets in different languages, use them as training data, and construct sentiment analysis model. A machine-learning algorithm is used to identify and extract characteristics such as adjectives, adverbs, and abstract nouns from each cleaned tweet. If the input text is not in English, the Google Machine Translator is utilized to convert it into English. A hybrid model called voting-based ensemble model which integrates Naive bayes, Multinomial Naive bayes, bernoulli's Naive bayes, Logistic Regression, Stochastic Gradient Descent, Support Vector Machines, and Maximum Entropy classifiers to resolve the ambiguous language. If, same word appears in both English and non-English it utilizes a hybrid model retrieved features to translate a tweet /string. The classifiers identify the sentiment of translated multilingual tweets and extended with prediction. © 2022 IEEE.

关键词： Support vector machines

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Prediction of Herbs with its benefits using Deep Learning techniques

Prediction of Herbs with its Benefits using Deep Learning Te...

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2022 International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022

作者： begum, M. Sharmila Haris, R. Vetrimaran, V. Raj, P. Ashwin B.Tech Computer Science and Engineering Pmist Tamil Nadu Vallam Thanjavur India

ISBN: (纸本)9781665478847

Automated plant identification is a very promising solution for bridging the taxonomic gap, which is receiving much attention from botany and computer science. As machine learning technology advances, more complex models have been proposed to automate crop identification. Herbal remedies are considered in the pharmaceutical industry due to fewer harmful side effects and less expensive than modern medicine. based on these data, many researchers have shown great interest in studying the recognition of natural herbal medicines. There are various possibilities for moving towards solid phase production capable of accurately discriminating medicinal plants in real time. In this project, efficient and reliable machine learning algorithms for plant catalogues using leaf images used in recent years are being studied. The review covers image processing techniques used to locate leaves and extract important leaf features from other machine learning steps. These deep learning stages are classified according to their function when it comes to discriminating leaf images based on common plant characteristics, i.e. shapes, ridges, textures and combinations of many elements. Then you get results using herbs with improved accuracy. The test results indicate that the proposed system provides an improved level of accuracy. © 2022 IEEE.

关键词： Deep neural networks

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IoT-Genomics Analysis for Personal Health with Cybergenomics and Cloud technology 10

IoT-Genomics Analysis for Personal Health with Cybergenomics...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Prabakaran, T. babu, A. Ramesh Hemalatha, S. Ramasamy, Jayabharathi Kovarasan, Rajesh Kambattan Elango, b. Joginpally B.R. Engineering College Department of Computer Science and Engineering Telangana Hyderabad India Vidya Vikas Institute of Engineering and Technology School of Computer Applications Karnataka Mysore India Tagore Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

Recent innovations at the convergence of genomics and the Internet of Things (IoT) have opened the way for an innovative strategy for administering individualized health care. This research study combines the potential of wearable health monitoring technologies with genetic insights to analyze the personal healthcare. A comprehensive knowledge of health dynamics may be achieved by seamlessly integrating real-time health data collected from IoT-enabled wearables with individual genetic profiles. Using algorithms for machine learning, connections between genetic differences and instantaneous health responses may be uncovered, paving the way for the development of individualized therapies and lifestyle recommendations. The suggested framework allows people to improve their health and gives medical professionals access to data-driven insights that can be used for the early diagnosis of diseases and the development of individualized treatment plans. The work that has been done sheds light on the revolutionary potential of merging genetics with the Internet of Things to establish a new paradigm of preventative and individualized medical treatment. © 2024 IEEE.

关键词： Genome

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A Secure Data Encryption Mechanism in Cloud Using Elliptic Curve Cryptography 2

A Secure Data Encryption Mechanism in Cloud Using Elliptic C...

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2nd IEEE International Conference on Intelligent and Innovative technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Sudha, I. Donald, Cecil Navya, S. Nithya, G. balamurugan, Manivannan Saravanan, S. Saveetha Institute of Medical and Technical Sciences - Simats Department of Computer Science and Engineering Saveetha School of Engineering Chennai India Department of Computer Science Bengaluru India Raghu Engineering College Department of Computer Science Engineering Visakhapatnam India Department of Cse V. S. B College of Engineering Technical Campus Coimbatore India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Mathematics Tamil Nadu Avadi India

ISBN: (纸本)9798350306415

Cloud computing is undergoing continuous evolution and is widely regarded as the next generation architecture for computing. Cloud computing technology allows users to store their data and applications on a remote server infrastructure known as the cloud. Cloud service providers, such Amazon, Rackspace, VMware, iCloud, Dropbox, Google's Application, and Microsoft Azure, provide customers the opportunity to create and deploy their own applications inside a cloud-based environment. These providers also grant users the ability to access and use these applications from any location worldwide. The subject of security poses significant challenges in contemporary times. The primary objective of cloud security is to establish a sense of confidence between cloud service providers and data owners inside the cloud environment. The cloud service provider is responsible for ensuring user data's security and integrity. Therefore, the use of several encryption techniques may effectively ensure cloud security. Data encryption is a commonly used procedure utilised to ensure the security of data. This study analyses the Elliptic Curve Cryptography method, focusing on its implementation in the context of encryption and digital signature processes. The objective is to enhance the security of cloud applications. Elliptic curve cryptography is a very effective and robust encryption system due to its ability to provide reduced key sizes, decreased CPU time requirements, and lower memory utilisation. © 2024 IEEE.

关键词： Cloud computing cryptography data security ECC encryption

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Enhancing Carbon Emission Tracking with Gemini: An AI Solution for Sustainable Development

Enhancing Carbon Emission Tracking with Gemini: An AI Soluti...

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AIML-Applications for engineering & technology (ICAET), International Conference on

作者： Annada Dash bhavini Mathur Piyusha Patil B.Tech in Computer Engineering Honors in Data Science and ML Cummins College of Engineering for Women Pune India B.Tech in Computer Engineering Cummins College of Engineering for Women Pune India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

This research explores the integration of advanced AI technologies, specifically Google's Gemini-1.5-Flash-001 model and Vertex AI, into the development of EcoTrack-a mobile application that helps users monitor and reduce their carbon emissions. At the core of this innovation is Ecobot, an AI-powered chatbot embedded within EcoTrack, designed to deliver personalized, actionable insights on sustainability. by leveraging Gemini's capabilities alongside real-time data through Vertex AI, Ecobot enhances user engagement by offering tailored advice on reducing their carbon footprint. The study illustrates how Ecobot processes various data points, including user input and environmental metrics, to generate precise recommendations for users looking to make more sustainable choices. The focus of this work is on the importance of scalable AI frameworks that can adapt to evolving sustainability goals while efficiently managing real-time data. Additionally, this paper addresses the ethical dimensions of using AI for environmental purposes, discussing its potential to drive meaningful action at both the individual and societal levels, contributing to the global effort to combat climate change.

关键词： Climate change Carbon dioxide Chatbots Real-time systems Mobile applications Artificial intelligence Sustainable development Recommender systems Monitoring

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Crime Against Women in India: Statistical Analysis Using Linear Regression

Crime Against Women in India: Statistical Analysis Using Lin...

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Advanced Computing & Communication technologies (ICACCtech), International Conference on

作者： Zarin Tasnim Mim Rittika Paul Mollah Md Foysal Fairuz Nowshin Tohfa Shah Abrar Mahi B-Tech of Computer Science and Engineering-IoT Jain (Deemed-to-be University) Bangalore India CMS Business School Jain (Deemed-to-be University) Bangalore India B-Tech of Computer Science and Engineering East Delta University Chattagram Bangladesh B-Tech of Computer Science and Engineering-Cyber Security Chandigarh University Delhi India

ISBN: (数字)9798331519056

ISBN: (纸本)9798331519063

The crime reports of offenses occurring against women all over India are increasing day by day. It has become one of today's most concerning socio-economic and cultural issues. Crime against women hampers the overall prosperity and development of the nation. This crime violates human rights, impacts women's physical and mental health, and becomes an educational barrier to women's empowerment. This paper surveys the reasons for the influence of reported Crime Against Women (CAW) in 35 states and union territories in India from 2001–2012. The dataset describes different types of Crime Against Women (CAW): rape, kidnapping, abduction, assault on women, insult to the modesty of women, cruelty by husband or relative. This paper also contains a report on the arrested rate for crimes against women in India from 2001–2012. According to the comparison between these two datasets, the person arrest rate is more than the crime against women rate in every state in India. We used machine learning-based linear regression analysis to format the relationship between two datasets, where crime against women is the dependent variable and people arrested rate is the independent variable. This paper discusses two types of linear regression: Simple Linear Regression and Multiple Linear Regression. The relation between these two datasets helps to predict the hot location of crimes, and the activeness of law enforcement regarding the crimes and encourages victims to take action. For the datasets, P-values, R-squared, and adjusted R-squared values are used to evaluate the statistically significant prediction in explaining the variation in crime rates. This prediction is used to reduce the rate of crime against women all over India.

关键词： Surveys Analytical models Statistical analysis Law enforcement Linear regression Mental health Machine learning Predictive models Unemployment Socioeconomics

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Challenges in Cyber Physical Social Systems and Internet of Things 5

Challenges in Cyber Physical Social Systems and Internet of ...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Revathi, S. Raja, J. Mohanraj, M. Malathi, K. Mallala, balasubbareddy Vidhya, R.G. B.S. Abdur Rahman Crescent Institute of Science and Technology Department of Computer Science Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai India Sri Eshwar college of engineering Department of Computer Science and Business Systems Coimbatore India Saveetha Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Chaitanya Bharathi Institute of Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Hkbk College of Engineering Department of Ece Bangalore India

ISBN: (纸本)9798331504403

This research analyses the complex dynamics of Cyber-Physical-Social Systems (CPSS), encompassing cyber-physical systems, cybersecurity, the Internet of Things (IoT), and social media. by exploring the interactions among these elements, this study analyses the vulnerabilities, risks, and potential benefits within the CPSS framework. This research study analyses the evolving landscape of cybersecurity by considering various aspects such as data integrity, privacy in the IoT era, and the influence of social media on user behaviour and influence dynamics. The study also introduces innovative strategies to enhance CPSS resilience, including methods to mitigate cyber threats and enhance overall system integrity. Additionally, we investigate how social media shapes CPSS behaviours, offering valuable insights into influence dynamics. This research advances the comprehensive understanding of CPSS to support future studies and advancements in the protection and improvement of interconnected systems. © 2024 IEEE.

关键词： Cyber-Physical Systems Cyber-Physical-Social Systems (CPSS) Cybersecurity Internet of Things (IoT) Social Media

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Streamlined breast Cancer Detection Using Ultra Wideband Radar without Invasive Measures 2

Streamlined Breast Cancer Detection Using Ultra Wideband Rad...

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2nd IEEE International Conference on Advances in Information technology, ICAIT 2024

作者： Arunachalam, P. Latha, P. Nessariose Jose, Naduvathezhath Godwin James, T. Prabahar Vivekanandan, G. Arya, Aayushi Department of Biomedical Engineering Vel Tech Rangarajan Dr. Sugunthala R&D Institute of Science and Technology No-42 Avadi-Vel Tech Road Vel Nagar TN Chennai India Department of Computer Sciences and Engineering V.S.B. Engineering Collage Karur India Denken Solutions India Department of Computer Science and Engineering India Department of CSE Sri Sairam Institute of Technology Chennai India School of Technology Woxsen University India

ISBN: (纸本)9798350383867

The paper proposes the new radar technology for the first stages of detection of the disease without the subjecting the patient to surgery. In this paradigm, such high-end radar technologies such as bistatic and monostatic patterns assist in identifying small tumours that are far from the surface of the breast tissue. One of them is applying the Ultra-Wideband pulses and the specific type is the seventh derivative Gaussian pulse. These pulses are shaped in a very strict manner, and which makes for sharp transition band pass Finite Impulse Response filters for the best data transfer and to eliminate interferences. The capability for sustaining practices recommended by the Federal Communication Commission concerning spectral standards allows signals to proceed safely through breast tissue. by modifying the amplitude and phase of the transmitted pulse in the study, it increases the power of the main lobe radiated as well as on the same note reduces the levels of sidelobes and losses in the channel as these are accomplished using radar antennas. It found that because of the characteristics of the backscattered signals, there are specific temporal and spectral patterns that can reliably indicate the existence of tumor. based on stimulations, there are huge disparities in electric field strength introduced in normal and malignant breast tissue, which supports the efficiency of the new radar system. Moreover, among the important information accumulating duties we can distinguish Specific Absorption Rate (SAR) which specifies the tumour place as it being illustrated by the raised energy absorption in breast malignant tissue relatively to healthy tissue. Similar experiments are also carried out with an actual heterogeneous breast phantom with tumors, and it can also be seen that the results are almost identical with the above simulation results and hence it can be understood that the enhanced radar technology is good enough for the earliest detection of breast cancer. At thi

关键词： Diseases

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