Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
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¿µ¹®Á¦¸ñ(English Title) |
Target Classification of Active Sonar Returns based on Convolutional Neural Network |
ÀúÀÚ(Author) |
±èÁ¤ÈÆ
Ãִ뼺
ÀÌÇü¼ö
ÀÌÁ¤¿ì
Jeong-Hun Kim
Dae-Sung Choi
Hyung-Soo Lee
Jung-Woo Lee
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¿ø¹®¼ö·Ïó(Citation) |
VOL 21 NO. 10 PP. 1909 ~ 1916 (2017. 10) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù µö ·¯´× ¾Ë°í¸®µëÀÌ ´Ù¾çÇÑ ºÐ¾ß¿¡ Àû¿ëµÇ¾î ÁÁÀº ¼º´ÉÀ» ³»°í ÀÖÁö¸¸, ¼Ò³ª½Ã½ºÅÛ¿¡´Â ¾ÆÁ÷ È°¹ßÈ÷ Àû¿ëµÇÁö ¾Ê°í ÀÖ´Ù. º» ³í¹®¿¡¼´Â ±â·Ú¿Í °°Àº ±Ý¼Ó ¹°Ã¼¿Í ¹ÙÀ§·ÎºÎÅÍ ¹Ý»çµÈ ´Éµ¿¼Ò³ª ¼ö½ÅÀ½ µ¥ÀÌÅ͸¦ µö ·¯´× ¾Ë°í¸®µëÀÇ ÇϳªÀÎ ÄÁº¼·ç¼Ç ½Å°æ¸ÁÀ¸·Î ½Äº°ÇÏ´Â ½ÇÇèÀ» ¼öÇàÇÏ¿´´Ù. °úÀûÇÕ ¹æÁö ¹× ¼º´É Çâ»óÀ» À§ÇØ µ¥ÀÌÅÍ È®ÀåÀ» ÇÏ¿´°í, È®Àå ¹× ÇÏÀÌÆÛÆĶó¹ÌÅÍ °ª º¯È¿¡ µû¸¥ ¼º´É º¯È¸¦ ºÐ¼®ÇÏ¿´´Ù. ÈƷõ¥ÀÌÅ͸¦ ¼ö½Å°¢µµ¿¡ µ¶¸³ÀûÀÎ °æ¿ì¿Í ÀÇÁ¸ÀûÀÎ °æ¿ì·Î ³ª´©¾î ½ÇÇèÀ» ¼öÇàÇÏ¿´°í, ±× °á°ú °¢°¢ 88.9%, 94.9%ÀÇ ¼º´ÉÀ» º¸¿´´Ù. ÀÌ´Â ÀÌÀü ¿¬±¸¿¡¼ Àΰø½Å°æ¸Á ¹× Support Vector Machine ¾Ë°í¸®µëÀ» Àû¿ëÇÏ¿© ¾òÀº ¼º´Éº¸´Ù ÃÖ´ë 4.5% Æ÷ÀÎÆ® Çâ»óµÇ¾ú´Ù.
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¿µ¹®³»¿ë (English Abstract) |
Recently, deep learning algorithms have good performance in various fields, but they are not actively applied to sonar systems. In this study, we carried out experiments to classify active sonar returns into a metal object such as a mine and a rock using a convolutional neural network which is one of the deep learning algorithms. Data augmentation is applied on this paper to avoid overfitting and increase performance. And we analyzed performance variation depending on hyperparameter value and change of the number of training data through data augmentation. The experiments are performed with two training data; an aspect-angle independent and an aspect-angle dependent. As a result, the performances are 88.9% and 94.9% in aspect-angle independent and dependent, respectively. These are up to 4.5% point higher than the performance obtained by applying artificial neural network and support vector machine algorithm in the previous study.
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Å°¿öµå(Keyword) |
´Éµ¿¼Ò³ª
µö ·¯´×
ÄÁº¼·ç¼Ç ½Å°æ¸Á
±â·Ú
Active Sonar
Deep Learning
Convolutional Neural Network
Mine
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