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  • 标题:COMPUTER VISION DETECTION OF SUBMERGED OBJECT THROUGH MACHINE LEARNING
  • 本地全文:下载
  • 作者:Rupinder Kaur ; Amita Kashyap ; Dushyant Kumar
  • 期刊名称:Ilköğretim Online/Elementary Education Online
  • 印刷版ISSN:1305-3515
  • 电子版ISSN:1305-3515
  • 出版年度:2021
  • 卷号:20
  • 期号:5
  • 页码:5013-5019
  • DOI:10.17051/ilkonline.2021.05.560
  • 语种:English
  • 出版社:Öğretmen Eğitimi Akademisi
  • 摘要:Object Recognition is a widely-held innovation that distinguishes examples inside an image. InordertoeliminatethebarriersinComputerVisioninnovation because of the disintegration of the RGB (Red-GreenBlue) constituents with the increment inside and out,it has been a need that the precision and effectiveness of recognizing any item submerged is ideal.Inthisresearch,, we direct Submerged Item Recognition utilizing AI through Tensor stream and image Handling alongside Fast-RCNN (Faster Region-Convolution Neural Network) as a calculation for execution. An appropriate climate will be made so that AI calculation will be utilized to prepare various pictures of the submerged object. Open source PC Vision has different capacities which can be utilized for the picture preparing needs when a picture is Open source PC Vision has different capacities which can be utilized for the image preparing needs when an object is acquire..
  • 关键词:RGB (Red-Green-Blue);Fast-RCNN (Faster Region-Convolution Neural Network);Computer Vision
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