Open AccessDeep learning based handwritten digit recognition in Android
Author(s) -
Yiqing Li
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2010/1/012044
Subject(s) - computer science , mnist database , digit recognition , intelligent word recognition , artificial intelligence , handwriting recognition , intelligent character recognition , speech recognition , pattern recognition (psychology) , android (operating system) , document processing , numerical digit , handwriting , deep learning , image (mathematics) , feature extraction , character recognition , artificial neural network , mathematics , arithmetic , operating system
Handwritten digit recognition refers to the recognition of handwritten digits written and printed on paper, and the recognition results are stored in the computing machine in the form of text. According to the characteristics of a handwritten digital image, based on the multi-layer perceptron method, this paper introduces the source and principle of handwritten digital image recognition in detail, and analyzes the steps, related functions and theories of handwritten digital image recognition in sequence. The proposed algorithm was validated on the handwritten dataset MNIST, and the model was evaluated and adjusted. Eventually, the trained model was migrated to Android.