DeepFruits: A Fruit Detection System Using Deep Neural Networks

@inproceedings{Sa2016DeepFruitsAF,
  title={DeepFruits: A Fruit Detection System Using Deep Neural Networks},
  author={Inkyu Sa and ZongYuan Ge and Feras Dayoub and Ben Upcroft and Tristan Perez and Chris McCool},
  booktitle={Sensors},
  year={2016}
}
This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it is a key element for fruit yield estimation and automated harvesting. Recent work in deep neural networks has led to the development of a state-of-the-art object detector termed Faster Region-based CNN (Faster R-CNN). We adapt this model, through… CONTINUE READING
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