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Abstract : Neonatal pain assessment is essential for infants concerning their health issues. There have been several studies to assess the pain of infants using image processing in the field of computer vision. In this paper, we propose a different approach to detect pain in infants that outperforms previous research in this field. We merged a face area-based feature collection method with a local binary pattern (LBP). Moreover, three different machine learning algorithms have been executed to find the best parameter to get a decent accuracy on the iCOPE dataset. The proposed method uses the SVM classifier to achieve 86% of testing accuracy compared to other methods.
Project : Neonatal facial features for detecting acute pain
using Machine Learning approach
When it comes to infants’ health, a neonatal pain assessment is critical. Several studies in the field of computer vision have used image processing to estimate the pain of neonates. A new strategy of detecting pain in newborns is executed in this project, and it outperforms earlier work in the field.
Two methods have been applied to get an accurate result and images from the Infant COPE dataset was used in both of the experiments.
1. A face area-based feature collection method with a local binary pattern (LBP) was merged. Different classifiers such as Random Forest and Linear Regression were used for testing the features and accuracy. The proposed method using the SVM classifier showed decent results compared to other methods.
2. Face area-based feature collection method with mediapipe framework and LBP is calculated. Furthermore, four different machine learning algorithms were used to determine the optimal parameter for achieving a decent level of accuracy on the iCOPE Dataset. In comparison to existing methods, the proposed method using the Random Forest classifier obtained 95% testing accuracy to detect faces.
Project : Face Recognition-based Attendance Management System
Fig : Class Diagram
Objectives
Objectives
>Making a platform to ease the attendance management.
>To overcome the problem of manual attendance and provide reliable record maintenance.
Project : Lab Result Management System ( Using Java)
The project's major goal is to provide the exam results in an understandable manner. This initiative helps educators and institutions provide outcomes in an easy-to-understand manner. The Teacher is the target user of the system. And by entering a user name and password for a secure login, teachers are given the ability to read, write, update, delete, and execute results. The administrator will have complete control over the result analyzer and will have the ability to read, write, and execute the results.
Technical Used:
Programming platform : Netbean.IDE
Front-end & Back-end: Java
Database : MySQL.
Project : Multi Vendor E-commerce Web Application
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