HANDWRITTEN DIGIT RECOGNITION USING VARIOUS MACHINE LEARNING ALGORITHMS AND MODELS
نویسندگان
چکیده
منابع مشابه
Handwritten digit Recognition using Support Vector Machine
Handwritten Numeral recognition plays a vital role in postal automation services especially in countries like India where multiple languages and scripts are used Discrete Hidden Markov Model (HMM) and hybrid of Neural Network (NN) and HMM are popular methods in handwritten word recognition system. The hybrid system gives better recognition result due to better discrimination capability of the N...
متن کاملUsing Generative Models for Handwritten Digit Recognition
We describe a method of recognizing handwritten digits by tting generative models that are built from deformable B-splines with Gaussian \ink generators" spaced along the length of the spline. The splines are adjusted using a novel elastic matching procedure based on the Expectation Maximization (EM) algorithm that maximizes the likelihood of the model generating the data. This approach has man...
متن کاملHandwritten Bangla Digit Recognition Using Deep Learning
In spite of the advances in pattern recognition technology, Handwritten Bangla Character Recognition (HBCR) (such as alpha-numeric and special characters) remains largely unsolved due to the presence of many perplexing characters and excessive cursive in Bangla handwriting. Even the best existing recognizers do not lead to satisfactory performance for practical applications. To improve the perf...
متن کاملPersian Handwritten Digit Recognition Using Particle Swarm Probabilistic Neural Network
Handwritten digit recognition can be categorized as a classification problem. Probabilistic Neural Network (PNN) is one of the most effective and useful classifiers, which works based on Bayesian rule. In this paper, in order to recognize Persian (Farsi) handwritten digit recognition, a combination of intelligent clustering method and PNN has been utilized. Hoda database, which includes 80000 P...
متن کاملComparison of Learning Algorithms for Handwritten Digit Recognition
This paper compares the performance of several classi er algorithms on a standard database of handwritten digits. We consider not only raw accuracy, but also rejection, training time, recognition time, and memory requirements.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Innovative Research in Computer Science & Technology
سال: 2020
ISSN: 2347-5552
DOI: 10.21276/ijircst.2020.8.4.16