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pil

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This project implements a CNN to classify CAPTCHA images. The code preprocesses images, applies Otsu's thresholding, and uses morphological transformations for character separation. The CNN model includes convolutional, batch normalization, dropout, and fully connected layers. Training, validation, and testing are performed on labeled datasets.

  • Updated May 30, 2024
  • Jupyter Notebook

The objective of this project is to demonstrate the implementation of object detection using the YOLO model, transformers library, and OpenCV. The provided Python script utilizes a pre-trained YOLO model (hustvl/yolos-tiny) for detecting objects in images.

  • Updated May 29, 2024
  • Jupyter Notebook

• Developed a Machine Learning Model, OHMEE, for recognizing and solving offline handwritten mathematical expressions (OHME), utilizing image data from documents, images, papers, and transcripts. • Developed user-defined mathematical methods to evaluate the solved string expressions, generating and plotting appropriate results.

  • Updated May 15, 2024
  • Python

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