CNN for Image Identification of Hiragana Based on Pattern Recognition using CNN

نویسندگان

چکیده

Hiragana is one of the letters in Japanese. In this study, CNN (Convolutional Neural Network) method used as identication method, while he preprocessing thresholding. Then carry out normalization stage and filtering to remove noise image. At training use maxpooling danse methods a liaison process, wherea testing using Adam Optimizer method. Here, we 1000 images from 50 hiragana characters with ratio 950: 50, 950 data data. Our experiment yield accuracy 95%.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Action Recognition with Image Based CNN Features

Most of human actions consist of complex temporal compositions of more simple actions. Action recognition tasks usually relies on complex handcrafted structures as features to represent the human action model. Convolutional Neural Nets (CNN) have shown to be a powerful tool that eliminate the need for designing handcrafted features. Usually, the output of the last layer in CNN (a layer before t...

متن کامل

CNN Based Hashing for Image Retrieval

Along with data on the web increasing dramatically, hashing is becoming more and more popular as a method of approximate nearest neighbor search. Previous supervised hashing methods utilized similarity/dissimilarity matrix to get semantic information. But the matrix is not easy to construct for a new dataset. Rather than to reconstruct the matrix, we proposed a straightforward CNN-based hashing...

متن کامل

A Modified Grasshopper Optimization Algorithm Combined with CNN for Content Based Image Retrieval

Nowadays, with huge progress in digital imaging, new image processing methods are needed to manage digital images stored on disks. Image retrieval has been one of the most challengeable fields in digital image processing which means searching in a big database in order to represent similar images to the query image. Although many efficient researches have been performed for this topic so far, t...

متن کامل

CNN-Based Automatic Urinary Particles Recognition

The urine sediment analysis of particles in microscopic images can assist physicians in evaluating patients with renal and urinary tract diseases. Manual urine sediment examination is labor-intensive, subjective and time-consuming, and the traditional automatic algorithms often extract the hand-crafted features for recognition. Instead of using the hand-crafted features, in this paper, we explo...

متن کامل

ذخیره 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: JAIS (Journal of Applied Intelligent System)

سال: 2021

ISSN: ['2502-9401', '2503-0493']

DOI: https://doi.org/10.33633/jais.v6i2.4586