Authors :
Abhishek Jha; Dr. Hitesh Singh; Dr. Vivek KumarDr; Dr. Kumud Saxena
Volume/Issue :
Volume 8 - 2023, Issue 6 - June
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/m5p9mtnn
DOI :
https://doi.org/10.5281/zenodo.8153358
Abstract :
Text on an image often contains important
information and directly carries high-level semantics in
academic institutions and financial institutions. This
makes it an important source of information and a
popular research topic. Many studies have shown that
CNN-based neural networks are very good at classifying
images, which is the foundation of text recognition. By
combining AI with the process of biometric
identification, a technique for text recognition in
academic institutions and financial institutions is
performed using Convolutional Neural Network (CNN).
Initially, preprocessing is done for making the document
image suitable for feature extraction. One hot encoding-
based feature extraction is performed. Two-dimensional
CNN is used to classify the final features.
Keywords :
Adam optimizer, AI, CNN, RMSprop, One hot encoding .
Text on an image often contains important
information and directly carries high-level semantics in
academic institutions and financial institutions. This
makes it an important source of information and a
popular research topic. Many studies have shown that
CNN-based neural networks are very good at classifying
images, which is the foundation of text recognition. By
combining AI with the process of biometric
identification, a technique for text recognition in
academic institutions and financial institutions is
performed using Convolutional Neural Network (CNN).
Initially, preprocessing is done for making the document
image suitable for feature extraction. One hot encoding-
based feature extraction is performed. Two-dimensional
CNN is used to classify the final features.
Keywords :
Adam optimizer, AI, CNN, RMSprop, One hot encoding .
