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Convolutional Neural Network-based System for Vehicle Front-Side Detection
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 Title & Authors
Convolutional Neural Network-based System for Vehicle Front-Side Detection
Park, Young-Kyu; Park, Je-Kang; On, Han-Ik; Kang, Dong-Joong;
This paper proposes a method for detecting the front side of vehicles. The method can find the car side with a license plate even with complicated and cluttered backgrounds. A convolutional neural network (CNN) is used to solve the detection problem as a unified framework combining feature detection, classification, searching, and localization estimation and improve the reliability of the system with simplicity of usage. The proposed CNN structure avoids sliding window search to find the locations of vehicles and reduces the computing time to achieve real-time processing. Multiple responses of the network for vehicle position are further processed by a weighted clustering and probabilistic threshold decision method. Experiments using real images in parking lots show the reliability of the method.
machine vision;deep learning;convolution neural network;vehicle detection;
 Cited by
컨볼루셔널 신경망과 케스케이드 안면 특징점 검출기를 이용한 얼굴의 특징점 분류,유제훈;고광은;심귀보;

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