MNIST Handwritten Digit Classification Based on Convolutional Neural Network with Hyperparameter Optimization-Reference-Cited by-同舟云学术

MNIST Handwritten Digit Classification Based on Convolutional Neural Network with Hyperparameter Optimization

Published:2023 Issue:3 Volume:36 Page:3595-3606
ISSN:1079-8587
Container-title:Intelligent Automation & Soft Computing
language:en
Short-container-title:

Author:

Shao Haijian,Ma Edwin,Zhu Ming,Deng Xing,Zhai Shengjie

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

https://www.techscience.com/iasc/v36n3/51937/pdf

Reference36 articles.

1. Exploring deep learning for view-based 3D model retrieval;Gao;ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM),2020

2. Adaptive fusion and category-level dictionary learning model for multiview human action recognition;Gao;IEEE Internet of Things Journal,2019

3. A review on digital image processing techniques for in-vivo confocal images of the cornea;Herrera-Pereda;Medical Image Analysis,2021

4. Review of digital image correlation application to large-scale composite structure testing;Janeliukstis;Composite Structures,2021

5. Pattern Recognition in Handwriting

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2. MNSIT Handwritten Digit Recognition using CNN;2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN);2024-07-03

3. Analysing Digits with Sequential Convolutional Neural Networks and Adam Optimizer;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

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5. Handwriting Classification of Numbers and Writing Data using the Convolutional Neural Network Model (CNN);2023 International Workshop on Artificial Intelligence and Image Processing (IWAIIP);2023-12-01