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Recognition of Handwritten Digit using Convolutional Neural Network in Python
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Abstract: In recent years, deep learning has become a very important part of artificial intelligence. With the growth of Artificial Neural Networks (ANN), deep learning has made machines much smarter and more capable. It is used in many areas such as health care, security, sports, robotics, and drones because it can solve many real-life problems. Among deep learning methods, the Convolutional Neural Network (CNN) is one of the most successful. It combines the ideas of ANN with modern deep learning methods. CNNs are widely used for pattern recognition, speech and face recognition, text and document classification, scene detection, and handwritten digit recognition.
Keywords: Handwritten Digit Recognition, Convolutional Neural Network,MNIST, Batch Normalization, Dropout, Data Augmentation, Learning Rate Scheduling, Deep Learning.
Keywords: Handwritten Digit Recognition, Convolutional Neural Network,MNIST, Batch Normalization, Dropout, Data Augmentation, Learning Rate Scheduling, Deep Learning.
How to Cite:
[1] Chandhan Sayee.R, Mohul Raj.T, Merlin.R. S, Sanjith Kumar.K, Nishanth.G. S, Monesh.V, M. Ulagammai, βRecognition of Handwritten Digit using Convolutional Neural Network in Python,β International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI: 10.17148/IJIREEICE.2025.131133
