Deep Learning Approaches for Textbook Recognition and Classification

In the digital era, the exponential growth of educational content has necessitated efficient methods for textbook recognition and classification. This paper explores the application of deep learning approaches to address the challenges associated with automating the recognition and categorization of textbooks. Leveraging Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), our proposed model not only identifies and extracts textual information from images of textbooks but also classifies them into predefined categories. Experimental results demonstrate the efficacy of the proposed deep learning approach in achieving high accuracy in textbook recognition and classification tasks. The model's robustness is tested across diverse datasets, showcasing its adaptability to various educational domains and publication styles.