Aim: Ā Ā Ā Ā Ā Ā Ā Ā To provide an automated system for the recognition of phishing websites through login URLs Abstract: Ā Ā Ā Ā Ā Ā Ā Ā Ā Phishing attacks
To develop a robust and accurate crop yield prediction system, crop yield statistics, leveraging advanced machine learning techniques to promote sustainable agricultural practices and enhance global food security.
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This study develops a machine learning model to classify heart disease into different severity levels. It analyzes patient data to improve diagnostic accuracy and support medical decisions.
Aim: Ā Ā Ā Ā Ā Ā To help doctors and practitioners in early prediction of diabetes using machine learning techniques.Ā Ā Abstract: Ā Ā Ā Ā Ā Ā Ā Ā Diabetes caused
Aim: Ā Ā Ā Ā Ā Ā Ā Ā This study aims to improve the accuracy of Ransomware Classification and Detection with Machine Learning Algorithms Ransomware Classification,
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The aim of this project is to propose a system to automate the process of fish population monitoring in aquaculture environments by utilizing the YOLOv8 deep learning-based object detection model, combined with image enhancement techniques.
To enhance DDoS attack detection by implementing a machine learning system with hyperparameter optimization and advanced prediction techniques, utilizing the CICIDS dataset to achieve high classification accuracy and improve network security.
Aim: Ā Ā Ā Ā Ā Ā Ā Ā Ā We proposed detecting Sleep Apnea Detection From Single-Lead ECG. The advancement of smart wearables technologies has provided a
Aim:Ā Ā Ā Ā Ā Ā Ā The aim of the project is to develop an automated, real-time attendance system using face recognition technology to enhance accuracy, eliminate manual errors, and streamline attendance tracking in institutions.