Indian New Currency Denomination Identification System with Audio Feedback Using Convolution Neural Networks for Visually Challenged and Elderly People

2020 ◽  
pp. 71-81
Author(s):  
Padma Vasavi Kalluru
Keyword(s):  
Neural Networks ◽  
Elderly People ◽  
Identification System ◽  
Audio Feedback ◽  
Convolution Neural Networks ◽  
Visually Challenged

scholarly journals Predicting the Crop Type and Region of Abundance using Machine Learning

2021 ◽  
Vol 9 (9) ◽  
pp. 1411-1416
Author(s):  
Mohd Khalid Shaikh
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Rural Area ◽  
Identification System ◽  
Plant Identification ◽  
Convolution Neural Networks ◽  
Technology Students ◽  
Modern Age ◽  
Crop Type ◽  
As If

Abstract: In this modern age of science too technology, students and people in big cities ignorance of many things, such as how we get food, how things are processed, and much more. We are just it focuses on the results we get, because of this morality our knowledge diminishes, as if we did not know the crops or the goods ourselves using. As we visit the rural area when we arrive beyond some kind of plant, we can't know that, so we have identified this place to resolve the problem of students, researchers and many more people by creating a plant identification system which will predict the type of crop and the location of abundance where the harvest is planted. Keywords: Crop Identification System, Convolution Neural networks, MobilenetV2.

An effective and accurate identification system of Mycobacterium tuberculosis using convolution neural networks

2019 ◽  
Vol 82 (6) ◽  
pp. 709-719 ◽  
Author(s):  
Chan‐Pang Kuok ◽  
Ming‐Huwi Horng ◽  
Yu‐Ming Liao ◽  
Nan‐Haw Chow ◽  
Yung‐Nien Sun
Keyword(s):  
Neural Networks ◽  
Mycobacterium Tuberculosis ◽  
Identification System ◽  
Accurate Identification ◽  
Convolution Neural Networks

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

A Novel Approach for Image Super Resolution Problems with Convolution Neural Networks

2017 ◽  
Vol 6 (4) ◽  
pp. 15
Author(s):  
JANARDHAN CHIDADALA ◽  
RAMANAIAH K.V. ◽  
BABULU K ◽  
◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Super Resolution ◽  
Convolution Neural Networks ◽  
Novel Approach ◽  
Image Super Resolution

Convolution Neural Networks for Traffic Sign Classification

2019 ◽  
Author(s):  
Rajashekar A ◽  
Shruti Hegdekar ◽  
Dikpal Shrestha ◽  
Prabin Nepal ◽  
Sujanb Neupane
Keyword(s):  
Neural Networks ◽  
Traffic Sign ◽  
Convolution Neural Networks ◽  
Traffic Sign Classification
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