MCS HOG Features and SVM Based Handwritten Digit Recognition System

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Journal of Intelligent Learning Systems and Applications

ISSN Print: 2150-8402
ISSN Online: 2150-8410
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"MCS HOG Features and SVM Based Handwritten Digit Recognition System"
written by Hamayun A. Khan,
published by Journal of Intelligent Learning Systems and Applications, Vol.9 No.2, 2017

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	An Efficient CNN Model for Automated Digital Handwritten Digit Classification
	2021

[2]	Un Système de Reconnaissance de Formes Basé sur une Approche Multi-Classifieurs
	2021

[3]	A Novel Feature Extractor Based on the Modified Approach of Histogram of Oriented Gradient
	2020

[4]	Handwritten Bengali Character Recognition Using Deep Convolution Neural Network
	2020

[5]	Hand Written Digit Recognition using Machine Learning
	2020

[6]	A Robust Handwritten Digit Recognition System Based on Sliding window with Edit distance
	2020

[7]	Image Classification using HOG and LBP Feature Descriptors with SVM and CNN
	2020

[8]	Handwritten Numeral Superposition to Printed Form Using Deep Auto-Encoder and Recognition Using Convolutional Neural Network
	2019

[9]	Pengenalan Tanda Tangan Menggunakan Histogram Of Oriented Gradients Dan Smooth Support Vector Machine
	2019

[10]	Recognition of Handwritten Characters based on Deep Learning with Tensor Flow
	2019

[11]	Fashion-MNIST Classification Based on HOG Feature Descriptor Using SVM
	International Journal of Innovative Technology and Exploring Engineering, 2019

[12]	Hybrid CNN-GRU model for high efficient handwritten digit recognition
	2019

[13]	Recognition of Handwritten Characters based on Deep Learning with Tensorflow
	2019

[14]	HANDWRITING RECOGNITION AND PREDICTION USING STOCHASTIC LOGISTIC REGRESSION
	2018

[15]	Efficient Handwritten Digit Classification using User-defined Classification Algorithm
	2018

[16]	Object Recognition in Python and MNIST Dataset Modification and Recognition with Five Machine Learning Classifiers
	2018

[17]	Bengali handwritten character recognition using deep convolutional neural network
	2017

[1]	Evolutionary Computing and Mobile Sustainable Networks Lecture Notes on Data Engineering and Communications Technologies, 2022 DOI:10.1007/978-981-16-9605-3_8

[2]	An Efficient CNN Model for Automated Digital Handwritten Digit Classification Journal of Information Systems Engineering and Business Intelligence, 2021 DOI:10.20473/jisebi.7.1.42-55

[3]	Hand Written Digit Recognition using Machine Learning 2020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT), 2020 DOI:10.1109/CSNT48778.2020.9115746

[4]	A Robust Handwritten Digit Recognition System Based on Sliding window with Edit distance 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 2020 DOI:10.1109/CONECCT50063.2020.9198385

[5]	Object Recognition in Python and MNIST Dataset Modification and Recognition with Five Machine Learning Classifiers Journal of Image and Graphics, 2018 DOI:10.18178/joig.6.1.10-20

[6]	Bengali handwritten character recognition using deep convolutional neural network 2017 20th International Conference of Computer and Information Technology (ICCIT), 2017 DOI:10.1109/ICCITECHN.2017.8281853

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