Abstract
At present, the handwritten digit recognition the problem has received more attention because it has a large standard and easy-to-use mature data set such as the MNIST data set, simple 0–9 digit recognition has been regarded as an entry problem in the field of computer vision. The paper Introduce the characteristics and applications of handwritten digit recognition at first. Then, the traditional research methods and their shortcomings is pointed out; the concept of deep learning are introduced. Taking the convolutional neural network as an example, the key technical characteristics of the convolutional neural network in detail is introduced. Finally, an example explain the application of convolutional neural network in handwritten digit recognition.
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Zhang, Q., Xu, S., Xu, Z. (2022). Handwritten Digit Recognition Application Based on Fully Connected Neural Network. In: Liu, Q., Liu, X., Chen, B., Zhang, Y., Peng, J. (eds) Proceedings of the 11th International Conference on Computer Engineering and Networks. Lecture Notes in Electrical Engineering, vol 808. Springer, Singapore. https://doi.org/10.1007/978-981-16-6554-7_9
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DOI: https://doi.org/10.1007/978-981-16-6554-7_9
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