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Deep Neural Networks for Image-Based Dietary Assessment
JoVE 杂志
工程学
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JoVE 杂志 工程学
Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

DOI:
10.3791/61906-v

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13:19 min

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March 13, 2021

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,
1Jožef Stefan International Postgraduate School, 2Computer Systems Department,Jožef Stefan Institute

Chapters

  • 00:00Introduction
  • 00:44Food Image Recognition with NutriNet
  • 05:08Food Image Segmentation with FCNs
  • 07:22Food Image Segmentation with HTC ResNet
  • 11:24Representative Results
  • 12:22Conclusion

Summary

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The goal of the work presented in this article is to develop technology for automated recognition of food and beverage items from images taken by mobile devices. The technology comprises of two different approaches - the first one performs food image recognition while the second one performs food image segmentation.

Tags

Image-based Dietary AssessmentDeep Neural NetworksFood Image RecognitionImage SegmentationFake FoodReal FoodFood ItemsGoogle Custom Search APIImage AugmentationCLoDSA LibraryImage RotationImage FlippingColor Noise

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