• Prof Arti Devmane
• Sharma Aditya Radheshyam
• Prachiti Yadav
• Vishnu Yelde,

This study contains Handwritten Character Recognition (HWR) at the intersection of human-written text and machine comprehension, offering a solution to convert handwritten text into digital formats. This abstract delves into the utilization of machine learning methodologies, particularly focusing on advanced deep learning techniques, to enhance the accuracy of HWR systems.The abstract first addresses the inherent challenges posed by the diverse nature of handwriting styles, underlining the significance of preliminary data pre-processing steps such as image segmentation. It emphasizes the pivotal role of Convolutional Neural Networks (CNNs) in HWR, citing their efficacy in extracting pertinent features from handwritten characters, thereby facilitating accurate recognition.

HWR,Machine learning,deep learning,CNN

"Handwritten Character Recognition using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.41-46, June-2024, Available :http://www.jetir.org/papers/JETIRGH06007.pdf

"Handwritten Character Recognition using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pp41-46, June-2024, Available at : http://www.jetir.org/papers/JETIRGH06007.pdf