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Day 88: Signature Recognition Using Machine Learning
The article provides a detailed walkthrough of building an automated Signature Recognition system using machine learning and computer vision, covering everything from data collection to deployment. Th
e system uses SVM classification with HOG features to distinguish between genuine and forged signatures, with practical applications in banking, legal, and educational sectors.

Reasons to Read -- Learn:

  • how to build a complete end-to-end signature verification system using computer vision and machine learning, with detailed code examples for each implementation step.
  • practical techniques for image preprocessing and feature extraction using HOG (Histogram of Oriented Gradients), which can be applied to various computer vision projects beyond signature recognition.
  • how to deploy a machine learning model as a Flask API service, including handling image uploads and returning verification results in a production environment.
  • publisher: @bhatadithya54764118
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