Character Recognition Using Linear Discriminant Analysis Method
This program implements character recognition using Linear Discriminant Analysis (LDA) method, achieving high recognition accuracy with multiple experimental results provided.
License Plate Localization, Character Segmentation, and Neural Network-based Character Recognition
Successfully implemented license plate localization, character segmentation, and neural network-based character recognition functionality with executable code implementation.
Neural Network-Based Character Recognition
This project implements character recognition using neural networks, a classic pattern recognition application. The source code trains a Backpropagation (BP) neural network to recognize 26 English letters, demonstrating key implementation details including network architecture, training methodology, and feature extraction techniques.
Source Code for Character Recognition System Using Backpropagation Neural Network
Source code implementation of a character recognition system utilizing Backpropagation Neural Network, capable of effective digit character recognition with configurable network parameters and training algorithms.
UCI Machine Learning Repository: Character Recognition Source Data
The UCI Machine Learning Repository provides source data for character recognition research, serving as a critical resource for developing OCR algorithms. Includes handwritten digits and printed letters datasets, essential for training machine learning models using techniques like CNN implementation and feature extraction methods.
License Plate Recognition System Using MATLAB: Detection, Segmentation and Character Recognition
MATLAB-based license plate detection, character segmentation, and character recognition system implementing computer vision and machine learning algorithms
Character Recognition: Algorithms and Implementation
Automated identification and segmentation of characters (letters, Chinese characters, and numerals) with technical implementation insights
Pattern Recognition Applications: Character Recognition, K-L Face Recognition, Iris Recognition, and Stroke Recognition
Code routines and learning materials for pattern recognition techniques including character recognition, K-L face recognition, iris recognition, and stroke recognition, featuring algorithm implementations and practical applications.
MATLAB Implementation of Deep Learning for Character Recognition
Deep learning application using convolutional neural networks for character recognition - a well-structured program implementation.
Character Recognition Using Convolutional Neural Networks
Character Recognition of A-Z 26 English Letters Using Convolutional Neural Networks with Implementation Details