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http://dx.doi.org/10.7471/ikeee.2018.22.4.1131

The Method of Abandoned Object Recognition based on Neural Networks  

Ryu, Dong-Gyun (Dept. of Electronics Engineering, Hanbat National University)
Lee, Jae-Heung (Dept. of Electronics Engineering, Hanbat National University)
Publication Information
Journal of IKEEE / v.22, no.4, 2018 , pp. 1131-1139 More about this Journal
Abstract
This paper proposes a method of recognition abandoned objects using convolutional neural networks. The method first detects an area for an abandoned object in image and, if there is a detected area, applies convolutional neural networks to that area to recognize which object is represented. Experiments were conducted through an application system that detects illegal trash dumping. The experiments result showed the area of abandoned object was detected efficiently. The detected areas enter the input of convolutional neural networks and are classified into whether it is a trash or not. To do this, I trained convolutional neural networks with my own trash dataset and open database. As a training result, I achieved high accuracy for the test set not included in the training set.
Keywords
deep learning; convolutional neural networks; difference image; abandoned object recognition; background estimation;
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