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Fast Object Detector Based on Convolutional Neural Networks

  • Karol PiaskowskiEmail author
  • Dominik Belter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10986)

Abstract

We propose a fast object detector, based on Convolutional Neural Network (CNN). The object detector, which operates on RGB images, is designed for a mobile robot equipped with a robotic manipulator. The proposed detector is designed to quickly and accurately detect objects which are common in small manufactories and workshops. We propose a fully convolutional architecture of neural network which allows the full GPU implementation. We provide results obtained on our custom dataset based on ImageNet and other common datasets, like COCO or PascalVOC. We also compare the proposed method with other state of the art object detectors.

Keywords

Objects detection Computer vision Deep neural networks 

Notes

Acknowledgments

This work was supported by the NCBR Grant no. LIDER/33/0176/L-8/16/NCBR/2017.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Control, Robotics and Information EngineeringPoznan University of TechnologyPoznanPoland

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