Corpus ID: 202572940

FoodTracker: A Real-time Food Detection Mobile Application by Deep Convolutional Neural Networks

@article{Sun2019FoodTrackerAR,
  title={FoodTracker: A Real-time Food Detection Mobile Application by Deep Convolutional Neural Networks},
  author={J. Sun and K. Radecka and Z. Zilic},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.05994}
}
We present a mobile application made to recognize food items of multi-object meal from a single image in real-time, and then return the nutrition facts with components and approximate amounts. Our work is organized in two parts. First, we build a deep convolutional neural network merging with YOLO, a state-of-the-art detection strategy, to achieve simultaneous multi-object recognition and localization with nearly 80% mean average precision. Second, we adapt our model into a mobile application… Expand
1 Citations
MyFood: A Food Segmentation and Classification System to Aid Nutritional Monitoring
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