Improvement of the performance of optical handwritten digit recognition by incorporating cross-domain autoencoder-based image to image translation technique

Digit Recognition ◽

Cross Domain ◽

Translation Technique ◽

Image Translation ◽

Advanced Approaches of Handwritten Digit Recognition Using Hybrid Algorithm

International Journal of communication and computer Technologies ◽

10.31838/ijccts/01.01.07 ◽

2019 ◽

Vol 1 (1) ◽

Keyword(s):

Hybrid Algorithm ◽

Digit Recognition ◽

2020 First International Conference of Smart Systems and Emerging Technologies (SMARTTECH) ◽

Feature Compression Based on Discrete Cosine Transform for Handwritten Digit Recognition

10.1109/smart-tech49988.2020.00021 ◽

2020 ◽

Author(s):

Ali Mohammed Almohammedi ◽

Irfan Ahmad

Keyword(s):

Discrete Cosine Transform ◽

Cosine Transform ◽

Digit Recognition ◽

ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357) ◽

Handwritten digit recognition using trace neural network with EKF training algorithm

10.1109/icecs.1999.812281 ◽

2003 ◽

Author(s):

Kwok-Wo Wang ◽

Sheng-Jiang Chang ◽

Chi-Sing Leung

Keyword(s):

Neural Network ◽

Training Algorithm ◽

Digit Recognition ◽

2010 Third International Conference on Intelligent Networks and Intelligent Systems ◽

On a Clustering Method for Handwritten Digit Recognition

10.1109/icinis.2010.130 ◽

2010 ◽

Author(s):

Ye Xu ◽

Wei Zhang

Keyword(s):

Clustering Method ◽

Digit Recognition ◽

Proceedings of the 11th International Conference on Distributed Smart Cameras - ICDSC 2017 ◽

A System on FPGA for Fast Handwritten Digit Recognition in Embedded Smart Cameras

10.1145/3131885.3131927 ◽

2017 ◽

Author(s):

Md Jubaer Hossain Pantho ◽

Festus Hategekimana ◽

Christophe Bobda

Keyword(s):

Smart Cameras ◽

Digit Recognition ◽

Embedded Smart Cameras ◽

Advances in Intelligent Systems and Computing - Recent Developments in Machine Learning and Data Analytics ◽

Feature Map Reduction in CNN for Handwritten Digit Recognition

10.1007/978-981-13-1280-9_14 ◽

2018 ◽

pp. 143-148 ◽

Cited By ~ 1

Author(s):

Sinjan Chakraborty ◽

Sayantan Paul ◽

Ram Sarkar ◽

Mita Nasipuri

Keyword(s):

Feature Map ◽

Digit Recognition ◽

Handwritten digit recognition system on an FPGA

2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC) ◽

10.1109/ccwc.2018.8301757 ◽

2018 ◽

Cited By ~ 1

Author(s):

Jiong Si ◽

Sarah L. Harris

Keyword(s):

Recognition System ◽

Digit Recognition ◽

2005 5th International Conference on Information Communications & Signal Processing ◽

Support Vector Machine Parameter tuning using Dynamic Encoding algorithm for handwritten digit recognition

10.1109/icics.2005.1689068 ◽

2006 ◽

Author(s):

Youngsu Park ◽

Sang Woo Kim ◽

Hyun-Sik Ahn

Keyword(s):

Support Vector Machine ◽

Parameter Tuning ◽

Support Vector ◽

Machine Parameter ◽

Digit Recognition ◽

Handwritten Digit ◽

Support Vector Machine Parameter

An improved feature extraction method for individual offline handwritten digit recognition

2010 8th World Congress on Intelligent Control and Automation ◽

10.1109/wcica.2010.5554355 ◽

2010 ◽

Cited By ~ 1

Author(s):

Wang Qinghui ◽

Yang Aiping ◽

Dai Wenzhan

Keyword(s):

Feature Extraction ◽

Extraction Method ◽

Feature Extraction Method ◽

Digit Recognition ◽

Advances in Intelligent Systems and Computing - Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) ◽

Machine Learning Techniques for Handwritten Digit Recognition

10.1007/978-3-030-44289-7_39 ◽

2020 ◽

pp. 414-426

Author(s):

Ahmad Taher Azar ◽

Alaa Khamis ◽

Nashwa Ahmad Kamal ◽

Brian Galli

Keyword(s):

Machine Learning ◽

Machine Learning Techniques ◽

Digit Recognition ◽

Learning Techniques ◽