Traditionally, blood group detection required invasive methods—sample collection, chemical reagents, and lab tests. We redefine this process by leveraging biometrics fingerprints as a …

A rapid, precise, and robust human blood group identification method is introduced for the fast and accurate identification of blood group in the case of emergency blood transfusion. Many …

Current methodologies involve invasive blood testing, requiring specialized facilities and trained personnel. This study proposes an innovative, non-invasive approach that leverages biometric …

This project focuses on automating blood group detection using image processing and deep learning techniques. Traditional blood group testing methods can be time-consuming and …

Based on the processing of images acquired from the NIR sensor the blood group of a person is known during emergency situations without any error. This Project proposes a noninvasive …

In the first mode, blood images are used to identify the blood group, utilizing the MobileNetV2 architecture—a lightweight yet highly effective convolutional neural network (CNN) model.

The medical diagnostic report in a blood group detection app is a crucial feature that provides users with detailed and structured insights into their blood group prediction results. This report …

Jun 17, 2024 · This paper aims to design and implement a prototype to detect and classify blood groups to avoid human error in blood group detection. The proposed system employs image …

In emergency medical situations, the timely retrieval of a patient’s blood group and medical history can be crucial for saving lives. This paper presents a biometric-based solution for blood group …

The proposed system for "Blood Group Prediction Using Thumb Fingerprint with Machine Learning" introduces an innovative approach to identifying blood groups without the need for …