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Current Result Document : 3 / 6
ÇѱÛÁ¦¸ñ(Korean Title) |
DNN°ú ½´ÆÛÇȼ¿À» ÀÌ¿ëÇÑ ½Ç³» °ø°£ ÀÎ½Ä |
¿µ¹®Á¦¸ñ(English Title) |
Indoor Space Recognition using Super-pixel and DNN |
ÀúÀÚ(Author) |
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¿ø¹®¼ö·Ïó(Citation) |
VOL 19 NO. 03 PP. 0043 ~ 0048 (2018. 06) |
Çѱ۳»¿ë (Korean Abstract) |
º» ³í¹®Àº DNN(Deep Neural Network)¿Í ½´ÆÛÇȼ¿À» ÀÌ¿ëÇÑ ½Ç³» °ø°£ ÀÎ½Ä ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. ¿µ»óÀ¸·ÎºÎÅÍ ½Ç³» °ø°£ ÀνÄÀ» À§ÇØ ¿ì¼± ¿µ»ó ºÐÇÒÀ» À§ÇÑ ¼¼±×¸àÅ×ÀÌ¼Ç ÇÁ·Î¼¼½º°¡ ÇÊ¿äÇÏ´Ù. À̸¦ À§ÇØ º» ³í¹®¿¡¼´Â Àû´çÇÑ Å©±â·Î ³ª´ ¼ö ÀÖ´Â ½´ÆÛ Çȼ¿ ¾Ë°í¸®ÁòÀ» ÀÌ¿ëÇØ ¼¼±×¸àÅ×À̼ÇÀ» ¼öÇàÇÑ´Ù. °¢ ¼¼±×¸ÕÆ®¸¦ ÀνÄÇϱâ À§ÇØ ¼¼±×¸ÕÆ®¸¶´Ù Á¦¾ÈÇÏ´Â ¹æ¹ýÀ» ÀÌ¿ëÇÏ¿© Ư¡À» ÃßÃâÇÑ´Ù. ÃßÃâµÈ Ư¡µéÀ» DNNÀ» ÀÌ¿ëÇÏ¿© ÇнÀÇÏ°í, ÇнÀÀ¸·ÎºÎÅÍ ÃßÃâµÈ DNN¸ðµ¨À» ÀÌ¿ëÇÏ¿© °¢ ¼¼±×¸ÕÆ®¸¦ ÀνÄÇÑ´Ù. ½ÇÇè °á°ú¸¦ ÅëÇØ Á¦¾ÈÇÏ´Â ¹æ¹ý°ú ±âÁ¸ÀÇ ¾Ë°í¸®Áò°úÀÇ ¼º´É ºñ±³ ºÐ¼®À» ÇÑ´Ù.
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¿µ¹®³»¿ë (English Abstract) |
In this paper, we propose an indoor-space recognition using DNN and super-pixel. In order to recognize the indoor space from the image, segmentation process is required for dividing an image Super-pixel is performed algorithm which can be divided into appropriate sizes. In order to recognize each segment, features are extracted using a proposed method. Extracted features are learned using DNN, and each segment is recognized using the DNN model. Experimental results show the performance comparison between the proposed method and existing algorithms.
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Å°¿öµå(Keyword) |
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Deep Learning
Super-pixel
Indoor-space recognition
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