Bangla Handwritten

Bangla handwritten character recognition (HWR) research focuses on developing accurate and efficient systems to automatically interpret handwritten Bangla text, a task complicated by the language's cursive nature and complex character formations. Current research heavily utilizes deep learning, particularly convolutional neural networks (CNNs) often ensembled for improved performance, and recurrent neural networks (RNNs) for sequence modeling, alongside techniques like knowledge distillation to address class imbalance. These advancements are crucial for improving access to information in Bangla, enabling applications such as automated document processing, address recognition from signboards, and broader advancements in optical character recognition (OCR) for low-resource languages.