Jitter Decomposition Meets Machine Learning: 1D-Convolutional Neural Network Approach

2021 ◽  
pp. 1-1
Author(s):  
Nan Ren ◽  
Zaiming Fu ◽  
Dandan Zhou ◽  
Dexuan Kong ◽  
Hanglin Liu ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Convolutional Neural Network ◽  
Network Approach ◽  
Neural Network Approach

scholarly journals Handwritten Digit and Text Recognition Based On Convolutional Neural Network Approach

2021 ◽  
Vol 23 (07) ◽  
pp. 1518-1525
Author(s):  
◽  
Vivekanandan S J ◽  
Dr Sivasubramanian S ◽  
◽  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Support Vector Machine ◽  
Convolutional Neural Network ◽  
Text Recognition ◽  
Support Vector ◽  
Network Approach ◽  
Neural Network Approach ◽  
Handwritten Digit

The goal of this undertaking is to foster a powerful penmanship acknowledgment methods utilizing ideas of Machine learning and PC vision. An expansion of MNIST digits dataset called the Emnist dataset has been utilized. It contains 62 classes with 0-9 digits and A-Z characters in both capitalized and lowercase. To recognize transcribed content and convert it into computerized structure utilizing Convolutional Neural Network and Support Vector Machine, shortened as CNN and SVM, for text arrangement and identification, has been made. Before that we pre-prepared the dataset and applied different channels over it. Our framework will perceive the content precisely utilizing tensorflow libraries.

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