Bengali OCR

Bengali Optical Character Recognition (OCR) research aims to develop accurate and efficient systems for converting handwritten and printed Bengali text into machine-readable format. Current efforts focus on improving accuracy using deep learning models like Convolutional Neural Networks (CNNs), transformers (e.g., ByT5), and YOLOv8, often incorporating techniques such as transfer learning, attention mechanisms, and ensemble methods to handle the complexities of the Bengali script and diverse document types. This work is crucial for preserving Bengali language resources, improving access to information, and enabling advancements in various applications, including document digitization, language processing, and automatic license plate recognition. The development of large, high-quality datasets, particularly for document layout analysis and diverse dialects, remains a key challenge and area of active research.