Image Finder Mobile Application Based on Neural Networks
Nowadays taking photos via mobile phone has become a very important part of everyone’s life. Almost each and every person who has a smart phone also has thousands of photos in their mobile device. At times it becomes very difficult to find a particular photo from thousands of photos, and it takes ti...
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2017-04-01
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doaj-1af93784e35246d5bfc8965d3d3949e72020-11-24T22:34:40ZengEduSoft publishingBrain: Broad Research in Artificial Intelligence and Neuroscience2068-04732067-39572017-04-0181516503Image Finder Mobile Application Based on Neural NetworksNabil M. Hewahi0Saira Rashid1University of BahrainUniversity of BahrainNowadays taking photos via mobile phone has become a very important part of everyone’s life. Almost each and every person who has a smart phone also has thousands of photos in their mobile device. At times it becomes very difficult to find a particular photo from thousands of photos, and it takes time. This research was done to come up with an innovative solution that could solve this problem. The solution will allow the user to find the required photo by simply drawing a sketch on the objects in the required picture, for example a tree or car, etc. Two types of supervised Artificial Neural Networks are used for this purpose; one is trained to identify the handmade sketches and other is trained to identify the images. The proposed approach introduces a mechanism to relate the sketches with the images by matching them after training. The experimentation results for testing the trained neural networks reached 100% for the sketches, and 84% for the images of two objects as a case study.http://www.edusoft.ro/brain/index.php/brain/article/view/670image recognition, neural networks, sketches |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nabil M. Hewahi Saira Rashid |
spellingShingle |
Nabil M. Hewahi Saira Rashid Image Finder Mobile Application Based on Neural Networks Brain: Broad Research in Artificial Intelligence and Neuroscience image recognition, neural networks, sketches |
author_facet |
Nabil M. Hewahi Saira Rashid |
author_sort |
Nabil M. Hewahi |
title |
Image Finder Mobile Application Based on Neural Networks |
title_short |
Image Finder Mobile Application Based on Neural Networks |
title_full |
Image Finder Mobile Application Based on Neural Networks |
title_fullStr |
Image Finder Mobile Application Based on Neural Networks |
title_full_unstemmed |
Image Finder Mobile Application Based on Neural Networks |
title_sort |
image finder mobile application based on neural networks |
publisher |
EduSoft publishing |
series |
Brain: Broad Research in Artificial Intelligence and Neuroscience |
issn |
2068-0473 2067-3957 |
publishDate |
2017-04-01 |
description |
Nowadays taking photos via mobile phone has become a very important part of everyone’s life. Almost each and every person who has a smart phone also has thousands of photos in their mobile device. At times it becomes very difficult to find a particular photo from thousands of photos, and it takes time. This research was done to come up with an innovative solution that could solve this problem. The solution will allow the user to find the required photo by simply drawing a sketch on the objects in the required picture, for example a tree or car, etc. Two types of supervised Artificial Neural Networks are used for this purpose; one is trained to identify the handmade sketches and other is trained to identify the images. The proposed approach introduces a mechanism to relate the sketches with the images by matching them after training. The experimentation results for testing the trained neural networks reached 100% for the sketches, and 84% for the images of two objects as a case study. |
topic |
image recognition, neural networks, sketches |
url |
http://www.edusoft.ro/brain/index.php/brain/article/view/670 |
work_keys_str_mv |
AT nabilmhewahi imagefindermobileapplicationbasedonneuralnetworks AT sairarashid imagefindermobileapplicationbasedonneuralnetworks |
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1725726223401746432 |