Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Deep Neural Network Based Approach for Retinal Disease Detection

Deep Neural Network Based Approach for Retinal Disease Detection

Sridhar, B.

Paperback

Business General

ISBN10: 6209360092
ISBN13: 9786209360091
Publisher: LAP Lambert Academic Publishing
Published: Nov 27 2025
Pages: 56
Weight: 0.19
Height: 0.13 Width: 6.00 Depth: 9.00
Language: English
This work focuses on the automated detection of retinal diseases such as Diabetic Retinopathy (DR) and Age-related Macular Degeneration (AMD) using MATLAB, GLCM (Gray Level Co-occurrence Matrix), and Deep Neural Networks (DNNs). Retinal images are processed through contrast enhancement, noise reduction, and segmentation techniques to extract meaningful features. GLCM is employed for texture-based feature extraction, while a deep learning model classifies the disease stages with high precision. To enhance practical usability, the system is integrated with hardware components such as Arduino, an LCD display, and a buzzer alert mechanism. The LCD screen displays the classification results, and the buzzer provides an alert if abnormalities are detected, ensuring immediate attention. This embedded approach makes the system suitable for real-time applications in hospitals, clinics, and remote healthcare centers. The project aims to offer an efficient, cost-effective, and accessible solution for early disease detection, potentially reducing vision loss through timely diagnosis and treatment.

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