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@article{177810,
        author = {S. RAVALI and R. CHARAN REDDY and N. SOWMYA and P. HARISH and Mrs M PRIYANKA REDDY},
        title = {Blood Group Detection using Deep Learning Techniques and building a Web Application to identify the Donors.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2641-2647},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177810},
        abstract = {Blood group identification plays a vital part in medical diagnostics and transfusion procedures. This design introduces a new system for detecting blood types using deep literacy and image processing. crucial point birth ways similar as sphere (acquainted FAST and Rotated BRIEF) and SIFT (Scale-steady point Transform) are used to enhance image quality and excerpt distinct features. These features are also fed into a Convolutional Neural Network (CNN), which is trained to directly classify blood types by feting unique visual patterns. The model demonstrates high delicacy and adaptability to varying image conditions, as proven through comprehensive testing on different datasets. This automated approach aims to simplify and accelerate blood group identification in clinical settings, enhancing both individual perfection and transfusion safety. Building upon this, the Blood Donor Identification System extends the functionality by incorporating patron enrollment and matching features. benefactors can register their blood type, health information, and contact details, while directors can manage data, search for compatible benefactors, and match them with donors grounded on blood group comity. The system provides a secure, stoner-friendly interface for both benefactors and directors, icing data sequestration and real- time access to critical information — especially precious during extremities. Overall, the integration of automated discovery with patron operation improves the effectiveness and trustability of blood donation and transfusion services. The Blood Donor Identification System builds upon the Blood Group Detection Using Image Processing design by introducing advanced features for managing, relating, and matching benefactors. It's designed to simplify the process of locating suitable blood benefactors by allowing individualities to register their blood type, contact information, and applicable health details. directors can efficiently manage this data, search for benefactors, and match them with donors grounded on blood group comity. At its core, the system offers a secure and stoner-friendly platform for commerce between benefactors and directors. directors can search for benefactors by blood group and view comprehensive biographies, while benefactors can register and modernize their information as demanded. The system emphasizes data sequestration, security, and real- time access s to patron information, significantly perfecting the effectiveness of exigency blood donation sweats.},
        keywords = {Transfusion remedy, medical diagnostics, Scale- steady point transfigure (SIFT), acquainted FAST and Rotated BRIEF (sphere) algorithms, point birth, Convolutional neural networks (CNN), Preprocessing, Differ, discrimination features, Adaptability to changes, Automated blood sample analysis, Case care, Transfusion operation},
        month = {May},
        }