Explainable Text Recognition and Classification using Neural Network and Fuzzy Logic

Nowadays, fuzzy logic and deep learning are useful methods for deriving incredibly precise predictions from complicated data sources. Neural networks have shown promise in generating captions and language translation. Convolutional neural networks are still the most popular approach for image classification problems, nevertheless. Furthermore, training models with several layers of interconnected artificial neurons is a component of deep learning, commonly referred to as deep neural networks. A neural network and fuzzy logic-based explainable text identification and detection model is proposed in this paper. It provides a detailed explanation of its steps.