Login / Signup

FRD-CNN: Object detection based on small-scale convolutional neural networks and feature reuse.

Wei LiKai LiuLin YanFei ChengYunQiu LvLiZhe Zhang
Published in: Scientific reports (2019)
Most of the recent successful object detection methods have been based on convolutional neural networks (CNNs). From previous studies, we learned that many feature reuse methods improve the network performance, but they increase the number of parameters. DenseNet uses thin layers that have fewer channels to alleviate the increase in parameters. This motivated us to find other methods for solving the increase in model size problems introduced by feature reuse methods. In this work, we employ different feature reuse methods on fire units and mobile units. We solved the problem and constructed two novel neural networks, fire-FRD-CNN and mobile-FRD-CNN. We conducted experiments with the proposed neural networks on KITTI and PASCAL VOC datasets.
Keyphrases
  • convolutional neural network
  • neural network
  • deep learning
  • wastewater treatment
  • machine learning
  • working memory
  • case control
  • solar cells