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  Published Paper Details:

  Paper Title

Low Power RTL Generation for Eye Disease Classification Using FPGA

  Authors

  Ms.R.Siva Dharshini,  Mr.S.Vengatesh Kumar,  Ms.M.Shahana

  Keywords

area, power consumption, delay, Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM).

  Abstract


This project focuses on the development of a low-power RTL (Register Transfer Level) generation model for eye disease classification using FPGA technology. The system integrates a graphical user interface (GUI) .The dataset used comprises eye disease images in .jpg or .png format. These images undergoes a preprocessing phase that includes resizing, noise removal, histogram equalization, gray-scale conversion, and normalization. Additionally, the Local Binary Pattern (LBP) algorithm is employed to capture relevant texture information from the images. For classification, the project utilizes the ResNet50 deep learning algorithm to analyze the image data. The final output of the model is translated into Verilog code for RTL simulation. This work aims to provide a hardware-efficient, low-power solution for real-time eye disease classification.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2506084

  Paper ID - 288433

  Page Number(s) - a729-a733

  Pubished in - Volume 13 | Issue 6 | June 2025

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Ms.R.Siva Dharshini,  Mr.S.Vengatesh Kumar,  Ms.M.Shahana,   "Low Power RTL Generation for Eye Disease Classification Using FPGA", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 6, pp.a729-a733, June 2025, Available at :http://www.ijcrt.org/papers/IJCRT2506084.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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