신경망 기반의 유기된 물체 인식 방법
The Method of Abandoned Object Recognition based on Neural Networks
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초록
본 논문에서는 합성곱 신경망을 이용한 유기된 물체 인식 방법을 제안한다. 유기된 물체 인식 방법은 영상 내에서 유기 물체에 대한 영역을 먼저 검출하며 검출된 영역이 있을 경우 해당 영역에 합성곱 신경망을 적용하여 어떤 물체를 나타내는지인식하는 과정을 거친다. 실험은 쓰레기 무단투기를 검출하는 응용 시스템을 통해 진행되었다. 실험 결과, 유기 물체에 대한영역을 효율적으로 검출하는 것을 볼 수 있었다. 검출된 영역은 합성곱 신경망으로 들어가 쓰레기인지 아닌지 분류되는 과정을 거쳤다. 이를 위해 자체적으로 수집한 쓰레기 데이터와 오픈 데이터베이스로 합성곱 신경망을 학습시켰다. 학습 결과, 학습에 포함되지 않은 테스트셋에 대해 약 97%의 정확도를 달성하였다
Abstract
This paper proposes a method of recognition abandoned objects using convolutional neural networks. The method firstdetects an area for an abandoned object in image and, if there is a detected area, applies convolutional neural networksto that area to recognize which object is represented. Experiments were conducted through an application system thatdetects illegal trash dumping. The experiments result showed the area of abandoned object was detected efficiently. Thedetected areas enter the input of convolutional neural networks and are classified into whether it is a trash or not. Todo this, I trained convolutional neural networks with my own trash dataset and open database. As a training result, Iachieved high accuracy for the test set not included in the training set.
참고문헌 (13)
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