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Introduction to AI
Artificial Intelligence (AI) simulates human intelligence in machines. Learn the core concepts, history, and applications of AI across industries.
Machine Learning Basics
Machine Learning is a subset of AI that teaches machines to learn patterns from data. Explore supervised, unsupervised, and reinforcement learning methods.
Deep Learning Overview
Deep Learning leverages neural networks with multiple layers to analyze complex patterns in data. Discover its use in image recognition, NLP, and robotics.
Enhanced Handwritten Character Recognition Using Combined MNIST and EMNIST Datasets
his study presents an improved approach to handwritten character recognition by integrating two widely used datasets: MNIST and the digits subset of EMNIST. While MNIST provides a standard benchmark for digit recognition, EMNIST extends the scope to include a larger variety of handwritten digit samples, offering additional diversity in writing styles. By combining these datasets, the model is exposed to a richer set of examples, enhancing its generalization capability. A compact Convolutional Neural Network (CNN) architecture is employed to efficiently learn patterns from the combined dataset. The trained model is evaluated using metrics such as accuracy, precision, recall, F1-score, and confusion matrices, demonstrating significant improvements in recognition performance over models trained on individual datasets. Furthermore, the trained model is optimized and converted to TensorFlow Lite format, enabling deployment on Android devices for real-time handwritten digit classification. This pipeline illustrates a practical and scalable method for mobile applications, educational tools, and digit-based input systems, providing both high accuracy and low computational overhead.
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