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Gesture-Driven Virtual Mouse: Empowering Accessibility through Hand Movements 5

Gesture-Driven Virtual Mouse: Empowering Accessibility throu...

引用

5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Julian, Anitha Suresh, Danush Ramyadevi, R. Saveetha Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350383522

The mouse has been a vital tool for human-computer interaction, with wired, wireless, and Bluetooth variations requiring power to connect a dongle to a PC. The proposed work uses the latest technology in computer vision and machine learning to recognize hand movements without needing extra equipment. Compatible with CNN models through mediapipe implementation, it enables various actions via various hand movements, all on a single computer. Utilizing a camera as the input device, the system relies on Python and OpenCV. The camera's output is displayed on the system's screen, allowing users to fine-tune their interactions. © 2024 IEEE.

关键词： computer vision gesture recognition hand gestures interaction Virtual mouse

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Image recognition based attendance system with spoof detection

Image recognition based attendance system with spoof detecti...

引用

International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Rakesh, K. Sumer Singh, B. Surya, A. Kaladevi, R. Department of Computer Science and Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9781032669663

In recent times numerous face recognition algorithms were used for the identification and authentication of a person to a system. The objective of this design is to recognize the human faces and forecast whether the detected faces are real or fake. Our design is mainly useful for institutional purpose to enhance and modernize the present attendance system into more effective and efficient than before. In this design, human face database is dynamically created by new user registration and this data is pumped into the recognizer algorithm. In this design we have added a spoofing discovery technology that’s used to judge whether the face in front of the machine is real or fake. The face presented by other media can be defined as false face, including hardcopy photographs, display screen of electronic products, etc. The dataset which are dynamically created while a new user is registered is stored in the database and whenever a new face is detected on the camera, it compares with the images that are already present in the database to mark the attendance. Also, the result image is generated with the chance of spoofing can be attained from the dataset pushed into the algorithm. Our proposed system has accuracy of above 97.6% and true positive rate is 99.7% in high precision model. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Database systems

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Detecting the violence from video using computer vision under 2dspatio temporal representations

Detecting the violence from video using computer vision unde...

引用

International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Srividhya, M. Ramyadevi, R. Vijaya Chamundeeswari, V. Department of Computer Science and Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9781032669663

A current hot topic in computer vision is action recognition in videos, particularly for the detection of aggression. The complexity of the 2D + t data produced by the proliferation of videos by a security camera or television material is what makes this work interesting. Modern techniques learn using 3D neural network approaches, which require data to train to produce discriminating features. This research intends to address topics such as cutting-edge techniques for video violence detection, datasets for real-time video violence detection framework development, and discussion and identification of unresolved concerns in the given subject. To overcome these restrictions, we offer throughout this piece a technique for putting videos into categories for violence recognition with a traditional 2D CNN. The methods comprise two parts.: (I) From an input video, we first construct several 2D spatial-temporal representations, (II) According to speculation, the new representations will feed CNN’s test/training data. The methodology by combining the separate conclusions from the video’s various 2D spatial-temporal representations and the categorization decision is made. An experiment on publicly available datasets with violent video demonstrates the usefulness of the suggested approach. © 2024, CRC Press/Balkema. All rights reserved.

关键词： computer vision

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Medicab emergency services

Medicab emergency services

引用

International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Sasikumar, S. Tejaswi, G. Sakthi Aishwarya, S. Subanu, K. Department of Computer Science and Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9781032669663

We created an Android app that allows users to access the medicab emergency services facility because there is a demise in India for a minute of the day. The concept suggests utilizing an app to let patients schedule transportation to hospitals. Patients can upload their current location and destination to the program or locate themselves. The patient can then evaluate the options and travel times of each transport across the area to choose the best one after the system displays nearby available ambulances. The application takes the ambulance driver to his destination, and he must confirm the reservation made. Administrators have access to all core data and are in charge of calling and querying operations. The app responds by pressing one button, at which point it notifies the nearby ambulance control center with the user’s information and location through GPRS. After collecting location coordinates from GPS devices, the software utilizes the Google Street View interface for application programming API to show ambulance details on the smart-phone’s Google Map client. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Hospitals

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Cogniwealth: Revolutionizing Finance, Empowering Investors, and Shaping the Future of Wealth Management 5

Cogniwealth: Revolutionizing Finance, Empowering Investors, ...

引用

5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Ramyadevi, R. Sasidharan, G. Saveetha Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350383522

Predicting financial growth for future investment is the system that is used to take all kinds of finance data and store that data in the vector database and the Llama 2 model or the system is considered as a financial advisor and if we ask some investment question or any related question towards finance it will search on the data user provided before and the response will be formatted such a way that the response is coming from a human advisor because it uses Natural language processing(NLP) to understand the human nature and respond to there emotion and the system can be used by fund researchers and a laymen user who want to invest money in any finance related sector and this system can be feed with users wanted data and for front-end the react js is used and it is a frontend library and it is single page application and it is component based library and for backend Django is used and Llama 2 and pinecone db for storing vectors of the collected data. © 2024 IEEE.

关键词： Embeddings Finance Assistant Llama-2 Semantic Search

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Customer Segmentation and Retention Strategies for Bank Using Machine Learning

Customer Segmentation and Retention Strategies for Bank Usin...

引用

2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Beedhi Reddy, Hemanth Kumar Vijay Anand, M. Saveetha Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350309140

Customer churn is a pressing problem faced by banks, affecting their revenues and customer satisfaction. To solve this problem, this study explores the use of machine learning, specifically Naive Bayes, Decision Trees, and AdaBoost classifiers, to predict and reduce customer churn. By leveraging these complex algorithms, banks can gain insight into customer behaviour and take proactive steps to retain valuable products as customers. The process starts with pre- processed data, model design and coding. This optimization can solve many problems such as excessive priority, missing data, categorical features, etc. Additionally, Data Analytics (EDA) and visualizations to gain a deeper understanding of customer segmentation;This allows to uncover important trends and good standards. When evaluating performance in the model, Focused on simple metrics such as recall and ROC- AUC scores. These metrics provide insight into the model's ability to accurately identify past customers while minimizing false positives. To improve the performance of model, hyperparameter tuning was performed to ensure that we achieved the highest accuracy. The Model adopt ROC-AUC curve to see the balance between true positive and negative value. This analysis provides a better understanding of the performance model, allowing to make informed decisions and strategies to manage the customer's quality. Actual and estimated loss status is displayed as an estimate of Customer's final model. This valuable information provides banks with the strategies necessary to identify potential credit losers and take the necessary steps to maintain their trust. © 2024 IEEE.

关键词： Sales

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Cyber Shield An AI-Driven Solution For Identifying Phishing Websites 10

Cyber Shield An AI-Driven Solution For Identifying Phishing ...

引用

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

作者： Ashwinkumar, V.K. Loganathan, V. Saveetha Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350353068

Phishing attacks, a prevalent form of social engineering and cyber threats, exploit human vulnerabilities to deceive internet users into divulging sensitive data for deceptive intentions. Among these, URL-based phishing attacks pose significant risks to individuals and organizations by manipulating trust in URLs to steal data or inject malware. This paper seeks to address this issue by employing machine learning models and deep neural networks trained on a dataset containing both malicious and normal URLs. Extracting relevant features from URL and website content, the models are evaluated and compared based on their predictive performance. This research contributes to enhancing cybersecurity measures against URL-based phishing attacks by leveraging advanced machine learning techniques for detection and prevention. © 2024 IEEE.

关键词： Websites

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Nutrigrow Using Gradient Boosting Regressor 1

Nutrigrow Using Gradient Boosting Regressor

引用

1st International Conference on Trends in engineering Systems and Technologies, ICTEST 2024

作者： Ashwini, A. Loganathan, V. Saveetha Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798350307795

ISBN: (纸本)9798350307795

In modern agriculture, the quest for enhanced crop yield and nutrient efficiency is paramount. Leveraging the Gradient Boosting Regressor algorithm, this research proposes a novel method to address this challenge. By analyzing historical rainfall data and soil fertility levels, the system predicts crop nutrient requirements, aiding farmers in making informed decisions on fertilizer application. Moreover, real-time weather forecasts are integrated to issue timely alerts, mitigating risks associated with adverse weather conditions. This holistic approach not only enhances crop yields but also minimizes nutrient wastage, contributing to environmental sustainability and economic viability. Through the synergy of advanced algorithms and agricultural data, this work offers a promising avenue for optimizing crop production and resource management in modern farming practices. © 2024 IEEE.

关键词： Potassium

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Emergency evacuation system

Emergency evacuation system

引用

International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Loganathan, V. Parveen Fathima, M. Poorvaja, A. Rajalakshmi, R. Department of Computer Science and Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9781032669663

As global population is increasing day by day, life expectancy rises, and the causes of death across the world is rapidly increasing. It is very common that we tend to rush to any known exit when fire breaks out but this is not necessarily the best option. Therefore, our project mainly focuses on developing a medium that notifies and alerts people to an exit that is comparatively safe. Our project uses IoT technology in order to track the fire location, then notify the people to leave out safely. The information regarding the risk is intimated to the people at the right time. Various sensors are used in order to detect gases, temperature etc. The information regarding the fire accident will be provided to the user in timely manner so that the people will be able to know about the risk that is likely to be happened. Thus, intimating the user regarding the risk by sending an alert message to their mobile phones can probably decrease the death rates of the people. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Gas temperature

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Progressing Breast Cancer Assessment: Precise Tumor Categorization through DenseNet201-based Deep Learning 2

Progressing Breast Cancer Assessment: Precise Tumor Categori...

引用

2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Logu, K. Thangaraj, S. John Justin Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350384277

In this groundbreaking research endeavor, we present a novel approach to breast cancer assessment, leveraging the power of deep learning and transfer learning techniques. Our methodology involves the fine-tuning of a pre-trained DenseNet201 model using the extensive BreakHis dataset, aiming to achieve precise categorization of breast cancer tumors. The primary objective of our study is to enhance the accuracy and reliability of breast cancer diagnosis through the utilization of state-of-the-art deep learning architectures. Employing transfer learning, we fine-tuned the pre-trained DenseNet201 model on the BreakHis dataset, a comprehensive and diverse collection of breast histopathological images. This dataset encompasses various benign and malignant breast tumor cases, providing a robust foundation for our model to learn intricate patterns and features. During the training phase, our model exhibited remarkable performance, achieving an impressive accuracy of 97.00%. The validation phase further reinforced the model's capabilities, yielding a validation accuracy of 92.00%. These compelling results underscore the efficacy of our approach in accurately categorizing breast tumors, thereby contributing to the advancement of breast cancer diagnostics. This research not only showcases the potential of deep learning in the field of medical image analysis but also emphasizes the importance of leveraging transfer learning to optimize model performance. The ability to discern subtle patterns in histopathological images enables our model to provide clinicians with reliable information for more accurate and timely breast cancer diagnosis. Our study signifies a significant step forward in the ongoing efforts to improve breast cancer assessment methodologies, with potential implications for enhancing patient outcomes through early and precise detection. The integration of advanced technologies, such as deep learning, into medical diagnostics holds promise for revolutionizing the w

关键词： Medical imaging

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