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Handwritten recognition system using transfer learning

 Department: Computer Science  
 By: usericon MIke_Tech_World  

 Project ID: 9632
   Rating:  (5.0) votes: 1
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   Price:₦5000
Abstract
The Handwritten Recognition System Using Transfer Learning is an advanced machine learning project that aims to accurately recognize handwritten characters by leveraging pre-trained models like VGG16 to achieve high accuracy and robustness. The project involves comprehensive data collection and preprocessing stages where images are extracted, normalized, and augmented to enhance model generalization. This is followed by model training, where a convolutional neural network is fine-tuned for the specific task of handwritten recognition, achieving over 97% accuracy on validation data. The trained model''s performance is rigorously evaluated using metrics like accuracy, precision, and recall. The system is implemented using Python with libraries such as TensorFlow, Keras, and Flask for model training and web deployment. The final product is deployed as a web service using Flask, allowing users to upload handwritten images and receive real-time predictions through a user-friendly interface. This project not only demonstrates the effectiveness of transfer learning in handwritten text recognition but also provides a robust and accessible tool for various real-world applications, highlighting the potential for future enhancements and broader applications in the domain....
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