Home >> Publication
°Ë»öÇÊµå °Ë»ö³»¿ë
°Ë»ö°á°ú : 664
ÇѱÛÁ¦¸ñ : È®»ê¸ðµ¨°ú AC-YOLO¸¦ ÀÌ¿ëÇÑ ÄÜÅÃÆ®·»ÁîÀÇ Áß½ÉÁ¡ ÀÌÅ» °Å¸® ÃøÁ¤
¿µ¹®Á¦¸ñ : Center Deviation Measurement of Contact Lens using Diffusion Model and AC-YOLO
Àú³ÎÁ¤º¸ : ÇØ´ç¾øÀ½   2024 ³â  1 ±Ç  1 È£  1  ~  44
³í¹®±¸ºÐ : ±¹³»±âŸ³í¹®Áý
¸ÞÀÎÀúÀÚ : ±è±â³²
¼­ºêÀúÀÚ : -
Å°¿öµå : -
ȍȍ :
ÇѱÛÁ¦¸ñ : [SWµî·Ï]¼ÒÇÁÆ®·»Áî ºñÀü°Ë»ç ÀΰøÁö´É ÇнÀ¿ë ÇÁ·Î±×·¥
¿µ¹®Á¦¸ñ : [SWµî·Ï]¼ÒÇÁÆ®·»Áî ºñÀü°Ë»ç ÀΰøÁö´É ÇнÀ¿ë ÇÁ·Î±×·¥
Àú³ÎÁ¤º¸ : Test   2024 ³â  7 ±Ç  1 È£  1  ~  1
³í¹®±¸ºÐ : SWµî·Ï
¸ÞÀÎÀúÀÚ : Test
¼­ºêÀúÀÚ : Test
Å°¿öµå : Test
Test
ȍȍ :
ÇѱÛÁ¦¸ñ : µö·¯´×À» ÀÌ¿ëÇÑ ±â°è°Ç°­ ¾ÈÁ¤¼º ¿¹Ãø
¿µ¹®Á¦¸ñ : Prediction of Machine Health Stability using Deep Learning
Àú³ÎÁ¤º¸ : ÇØ´ç¾øÀ½   2023 ³â  1 ±Ç  1 È£  1  ~  55
³í¹®±¸ºÐ : ±¹³»±âŸ³í¹®Áý
¸ÞÀÎÀúÀÚ : CHHOL DIMANG
¼­ºêÀúÀÚ : -
Å°¿öµå : -
ȍȍ :
ÇѱÛÁ¦¸ñ : [SWµî·Ï]¼ÒÇÁÆ®·»Áî ºñÀü°Ë»ç ÀΰøÁö´É ÇнÀ¿ë ÇÁ·Î±×·¥
¿µ¹®Á¦¸ñ : [SWµî·Ï]¼ÒÇÁÆ®·»Áî ºñÀü°Ë»ç ÀΰøÁö´É ÇнÀ¿ë ÇÁ·Î±×·¥
Àú³ÎÁ¤º¸ : swµî·Ï   2023 ³â  1 ±Ç  1 È£  1  ~  1
³í¹®±¸ºÐ : SWµî·Ï
¸ÞÀÎÀúÀÚ : ±è¼ºÈÆ
¼­ºêÀúÀÚ : -
Å°¿öµå : -
-
ȍȍ :
ÇѱÛÁ¦¸ñ : [SWµî·Ï] ¼ÒÇÁÆ®·»Áî ºÒ·®Å½Áö AIµö·¯´× ºñÀü°Ë»ç ÇÁ·Î±×·¥
¿µ¹®Á¦¸ñ : [SWµî·Ï] ¼ÒÇÁÆ®·»Áî ºÒ·®Å½Áö AIµö·¯´× ºñÀü°Ë»ç ÇÁ·Î±×·¥
Àú³ÎÁ¤º¸ : swµî·Ï   2023 ³â  1 ±Ç  1 È£  1  ~  1
³í¹®±¸ºÐ : SWµî·Ï
¸ÞÀÎÀúÀÚ : ±è¼ºÈÆ
¼­ºêÀúÀÚ : -
Å°¿öµå : -
-
ȍȍ :
ÇѱÛÁ¦¸ñ : [SWµî·Ï]¼ÒÇÁÆ®·»Áî ºÒ·®ºÐ·ù ¸ðµ¨¿ë annotation ÇÁ·Î±×·¥
¿µ¹®Á¦¸ñ : [SWµî·Ï]¼ÒÇÁÆ®·»Áî ºÒ·®ºÐ·ù ¸ðµ¨¿ë annotation ÇÁ·Î±×·¥
Àú³ÎÁ¤º¸ : swµî·Ï   2023 ³â  1 ±Ç  1 È£  1  ~  1
³í¹®±¸ºÐ : SWµî·Ï
¸ÞÀÎÀúÀÚ : ±è¼ºÈÆ
¼­ºêÀúÀÚ : -
Å°¿öµå : -
-
»ç»ç : Grand ICT ¿¬±¸¼¾ÅÍ(ÃæºÏ´ë)
ÇѱÛÁ¦¸ñ : [SWµî·Ï]Process Contral Block ½Ç½Ã°£ µ¥ÀÌÅÍ gathering ÇÁ·Î±×·¥
¿µ¹®Á¦¸ñ : [SWµî·Ï]Process Contral Block ½Ç½Ã°£ µ¥ÀÌÅÍ gathering ÇÁ·Î±×·¥
Àú³ÎÁ¤º¸ : swµî·Ï   2023 ³â  1 ±Ç  1 È£  1  ~  1
³í¹®±¸ºÐ : SWµî·Ï
¸ÞÀÎÀúÀÚ : ÁÖÀÎ
¼­ºêÀúÀÚ : -
Å°¿öµå : -
-
»ç»ç : Grand ICT ¿¬±¸¼¾ÅÍ(ÃæºÏ´ë)
ÇѱÛÁ¦¸ñ : SOIF-DN: Preserving Small Object Information Flow With Improved Deep Learn...
¿µ¹®Á¦¸ñ : SOIF-DN: Preserving Small Object Information Flow With Improved Deep Learn...
Àú³ÎÁ¤º¸ : IEEE Access   2023 ³â  11 ±Ç  1 È£  1  ~  15
³í¹®±¸ºÐ : SCI(E)
¸ÞÀÎÀúÀÚ : IN JOO
¼­ºêÀúÀÚ : SUNGHOON KIM, GINAM KIM, KWAN-HEE YOO
Å°¿öµå : Defect detection, feature fusion, feature pyramid, printed circuit board (PCB), small object detection, small object information flow (SOIF-DN), deep learning
Defect detection, feature fusion, feature pyramid, printed circuit board (PCB), small object detection, small object information flow (SOIF-DN), deep learning
ȍȍ : This work was supported in part by the Ministry of Science and Information Communication Technology (MSIT), South Korea, through the Grand Information Technology Research Center Support Program, Supervised by the Institute for Information and Communications Technology Planning and Evaluation (IITP), under Grant IITP-2023-2020-0-01462.
ÇѱÛÁ¦¸ñ : ¸Ó½Å·¯´×À» »ç¿ëÇÑ À¾¡¤¸é Áö¿ª ÁßÇлýÀÇ °íµîÇб³ ÁøÇÐ ¿¹Ãø
¿µ¹®Á¦¸ñ : Middle School Students in Rural Area Using Machine Learning High School Graduati...
Àú³ÎÁ¤º¸ : Çѱ¹ÄÜÅÙÃ÷ÇÐȸ   2023 ³â  23 ±Ç  10 È£  423  ~  433
³í¹®±¸ºÐ : ±¹³»Àü¹®ÇмúÁö
¸ÞÀÎÀúÀÚ : ÁÖ¼ºÁ¾
¼­ºêÀúÀÚ : ±è¼ºÈÆ, ·ù°üÈñ
Å°¿öµå : À¾¡¤¸é ´ÜÀ§ ÁßÇлýµéÀÇ Æ¯¼º µ¥ÀÌÅÍ, ¸Ó½Å·¯´×, °íµîÇб³ ÁøÇÐ ¿¹Ãø, Á¤È®µµ
The Characteristic Data of Middle School Students in Eup and Myeon Units, Machine Learning, Predict Students Entrance into High School, Accuracy∣
»ç»ç : º» ¿¬±¸´Â °úÇбâ¼úÁ¤º¸Åë½ÅºÎ ¹× Á¤º¸Åë½Å±âȹÆò°¡¿øÀÇ Áö¿ªÁö´ÉÈ­Çõ½ÅÀÎÀç¾ç¼º(Grand ICT¿¬±¸¼¾ÅÍ) »ç¾÷ÀÇ ¿¬±¸°á°ú·Î ¼ö ÇàµÇ¾úÀ½¡± (IITP-2023-2020-0-01462)
ÇѱÛÁ¦¸ñ : SCE-LSTM: Sparse Critical Event-Driven LSTM Model with Selective Memorization f...
¿µ¹®Á¦¸ñ : SCE-LSTM: Sparse Critical Event-Driven LSTM Model with Selective Memorization f...
Àú³ÎÁ¤º¸ : agriculture   2023 ³â  13 ±Ç  2044 È£  1  ~  22
³í¹®±¸ºÐ : SCI(E)
¸ÞÀÎÀúÀÚ : Ga-Ae Ryu
¼­ºêÀúÀÚ : Tserenpurev Chuluunsaikhan, Aziz Nasridinov, HyungChul Rah and Kwan-Hee Yoo
Å°¿öµå : sparse critical event-driven LSTM (SCE-LSTM); forecasting; pork consumption; unstructured big data
sparse critical event-driven LSTM (SCE-LSTM); forecasting; pork consumption; unstructured big data
ȍȍ : This work has been supported by the MSIT (Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2023-2020-0-01462) su- pervised by the IITP (Institute for Information & communications Technology Planning & Evalua- tion), and the Basic Science Research Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant number:2020R1I1A1A01071884).
1234567891011121314151617181920...