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  1. University of Computer Studies, Yangon
  2. Conferences

Object Detection Using Regions with Convolutional Neural Networks (R-CNN)

http://hdl.handle.net/20.500.12678/0000003460
http://hdl.handle.net/20.500.12678/0000003460
3f126502-6657-4b9e-a9e8-6b73419b6d3f
89b1fb85-a102-4867-bc2f-3ddd3b72783a
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ICCA ICCA 2019 Proceedings Book-pages-212-217.pdf (1391 Kb)
Publication type
Article
Upload type
Publication
Title
Title Object Detection Using Regions with Convolutional Neural Networks (R-CNN)
Language en
Publication date 2019-02-27
Authors
Cherry, Hnin
Sein, Myint Myint
Description
With an importance of artificial intelligence intoday’s world, deep learning technology hasdeveloped very powerful in solving many problems invarious fields that is included in speech recognition,natural language processing, computer visiontechnologies, image processing and video, anddifferent kinds of multimedia. Due to the developmentof deep learning approach, visual recognitionsystems have achieved in good performance. With theincrease of smart application in visual recognition,powerful object detection systems are necessarilyneeded. In detecting objects, object classification isas a very important role. Deep Neural Network(DNN) can greatly achieved in classifying objects. Inthe experiment, object detection system for stop signis implemented by using Regions with ConvolutionalNeural Networks (R-CNN) that is used to classifyimage regions included in an image. The systemintended to provide object detection accurately.
Keywords
Object Detection, Deep Neural Network (DNN), Convolutional Neural Networks (CNN), Regions with Convolutional Neural Networks (RCNN)
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1208
Journal articles
Seventeenth International Conference on Computer Applications(ICCA 2019)
Conference papers
Books/reports/chapters
Thesis/dissertations
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