Classification of Soya Beans Based Image Processing Techniques and Artificial Neural Network

2018 ◽  
Vol 26 (6) ◽  
pp. 1-9 ◽  
Author(s):  
Umar Abdulhamid ◽  
Simon Daniel ◽  
Usman Babawuro
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Artificial Neural Network ◽  
Image Processing Techniques ◽  
Artificial Neural ◽  
Processing Techniques

scholarly journals Screening of Tuberculosis Using Artificial Neural Network

2020 ◽  
Vol 3 (11) ◽  
pp. 145-149
Author(s):  
A. Anand Kumar ◽  
T. Mani ◽  
S. Gokulnath ◽  
S. K. Kabilesh ◽  
K. Dinakaran ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Artificial Neural Network ◽  
Feature Extraction ◽  
Bacterial Disease ◽  
Image Processing Techniques ◽  
Neural Organization ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Processing Techniques

Tuberculosis is an infectious bacterial disease that most commonly affects the lungs. This paper reviews, screening of tuberculosis in chest radiograph images using an artificial neural network (ANN). Implementing image processing techniques having segmentation, feature extraction from chest radiographs, at that point building up a fake neural organization for programmed characterization dependent on back proliferation calculation to group tuberculosis accurately. The performance was evaluated using SVM and ANN classifiers regarding exactness, review, and precision. The trial results Confirm the effectiveness of the proposed strategy that gives great Classification proficiency.

scholarly journals AN ALGORITHM TO ANALYZE STRENGTH OF CAPTCHA

2012 ◽  
pp. 140-145
Author(s):  
AJINKYA KASHINATH PARBHANE ◽  
ANAJALI .A. CHANDAVALE ◽  
A.M. SAPKAL
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Artificial Neural Network ◽  
Character Recognition ◽  
Experimental Result ◽  
The Internet ◽  
Image Processing Techniques ◽  
Artificial Neural ◽  
Processing Techniques

CAPTCHA stands for Completely Automated Public Turing Tests to Tell Computers and Humans Apart. The CAPTCHAs have been widely used across the Internet to defend against undesirable and malicious bot programs. It was observed that an alarming number of CAPTCHAs could be broken by the technique of Image Processing and Artificial Neural Network. Many Researchers have tried to break a CAPTCHA so as to design robust CAPTCHA , but it is essential to generate a strong CAPTCHA that will resist bot attack. This paper has proposed algorithm to analyze the strength of CAPTCHAs using simple image processing techniques such as Preprocessing, Segmentation and Character recognition which in turn helps to improve the robustness and usability of CAPTCHA in Internet System. The experimental result shows the proposed algorithm gives 75 % accuracy to analyze the strength of CAPTCHA.

scholarly journals APLICAÇÃO DE REDES NEURAIS CONVOLUCIONAIS NO RECONHECIMENTO DE CARACTERES EM PLACAS INFORMATIVAS JAPONESAS

2021 ◽  
Vol 13 (2) ◽  
pp. 12-24
Author(s):  
Rafael Yuji Hirata Furusho ◽  
Francisco Assis da Silva ◽  
Leandro Luiz de Almeida ◽  
Danillo Roberto Pereira ◽  
Mário Augusto Pazoti ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Edge Detection ◽  
Convolutional Neural Network ◽  
Mathematical Morphology ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Processing Techniques ◽  
Processing Techniques

Unlike most Western countries, which have a Latin-derived base alphabet, Japan has two syllabic alphabets called Hiragana and Katakana, and a Chinese alphabet, called Kanji. The vast differences in the writing of these Eastern alphabets to Western alphabets, Western alphabet-based OCR algorithms tend not to efficiently detect Japanese characters. This work contributes to a methodology applying digital image processing techniques, such as color range-based segmentation, edge detection and mathematical morphology techniques, to detect Japanese traffic informationalplates correctly the perspective and segment the characters contained in it. A convolutional neural network wasused to perform the classification of Hiragana characters contained in the segmented plates, withaccuracyof 94.37%.

Research of the cold resistance of metals by indentation with registration of an acoustic emission signal

2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Low Temperatures ◽  
Cold Resistance ◽  
Emission Signal ◽  
Impact Bending ◽  
Artificial Neural

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]

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