Dinthisrang Daimary

Papers

Total Citations

101

H-Index

About

Dr. Dinthisrang Daimary has made significant contributions at the intersection of deep learning and pattern recognition, with a primary focus on handwritten character recognition and optical character recognition (OCR) systems. His most influential work, "Handwritten Character Recognition from Images using CNN-ECOC" (2020), which has garnered over 100 citations, introduced a novel hybrid approach combining Convolutional Neural Networks with Error-Correcting Output Codes (ECOC) to enhance classification accuracy for handwritten scripts. This research addresses critical challenges in OCR, particularly the variability and complexity of handwritten characters, and has been widely recognized for advancing robust recognition frameworks. Dr. Daimary’s work is notable for bridging traditional machine learning techniques with modern deep learning architectures, offering practical solutions for digitizing handwritten documents. His contributions have implications for automated document processing, assistive technologies, and historical manuscript preservation. With a growing citation impact and a focus on real-world applicability, Dr. Daimary continues to be an emerging voice in the fields of computer vision and intelligent character recognition, inspiring further research into efficient, scalable OCR systems.