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30.
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(2005.3~2006.6 ªL«ØµØ ¡B²ø«T«Û¡BªL¨Î¼z¡B¤ý«³ªN¡B¦¶¼ü·¶)
31.
Microsoft Office¡BOpen Office¡BStar Office ¿ì¤½«Ç¤å®Ñ³B²z³nÅ餧¤ñ¸û(2004.9~20056 ¹ù¶iªQ)
32.
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33.
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34.
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35.
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36.
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37.
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38.
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·¨´Â´Iµ¥¤û) (¤E¤Q¤@¦~«×²¦·~±MÃD¦¨ªG®i²Ä¤T®iÄý³õ²Ä¤G¦W)
39.
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40.
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41.
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§ùÀA¨Kµ¥¤û)
42.
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43.
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(¤K¤Q¤E¦~«×²¦·~±MÃD¦¨ªG®i¹ê¥Î»ùȼú)
45.
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46.
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47.
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48.
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49.
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50.
¾÷¨®±Æ®ðÀË´ú¸ê°TºÞ²z¨t²Î¡X¥D±q¬[ºc(1997.2~1998.6³¯¶Ç°êµ¥¤û)
51.
¾÷¨®±Æ®ðÀË´ú¸ê°TºÞ²z¨t²Î¡X¦h¼h¬[ºc(1997.2~1998.6ªL¹D¤¸µ¥¤û)
52.
¾÷¨®±Æ®ðÀË´ú¸ê°TºÞ²z¨t²Î¡X¼·±µ³s½u(1997.2~1998.6³¯¾§ªLµ¥¤û)
53.
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54. ¤H©Ê¤Æø¹Ï¨t²Î(1996.3~1997.6±ç·ç¥Éµ¥¤û)
55. °ê¬ì·|©ïÀYÅã¥Ü¾¹Åã¥Ü¶´yø¨t²Î(1995.3~1996.6S¬üµ^µ¥¤Q¤Kû)
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No |
½×¤åÃD¥Ø |
«ü¾É´Á¶¡ |
«ü¾É ¬ã¨s¥Í |
¥Ø«eª¬ºA |
1. |
¥H¤H®æ¯S½è»P²Õ´¤å¤Æ±´°Q°ª¬ì§Þ²£·~¤ºª¾ÃѤÀ¨É¤Î²Õ´ÁZ®Ä¤§¬ã¨s The
study of the interrelationships between knowledge sharing and organizational performance
from the perspectives of personality traits and organizational culture in
high technology industry |
2004/09~2006/06 |
ªL©s¾W |
´Â¶§¬ì§Þ¤j¾Ç ¸ê°T¬ì§Þ¬ã¨s©Ò³Õ¤h¯Z |
2. |
¥HÃC¦â¼Ë¦¡»PªÅ¶¡¼Ë¦¡¬°¥Dªº¼v¹³·j´M¨t²Î Image Retrieval System based on Color-Pattern and
Spatial-Pattern |
2004/09~2006/06 |
¶À¤å±l |
¥xÆW°ò¦¶}µo ¬ì§ÞªA¥÷¦³¤½¥q |
3. |
´Ó°ò©ó¦h¶¥ÃC¦â¯S¼x»y·N®ø¶OªÌ¼v¹³À˯Á¨t²Î Semantic Consumer Image Retrieval System Based on Multi-layer Color Features |
2005/09~2007/06 |
»Â©É¬Â |
°T³s¬ì§Þ |
4. |
Â^¨ú¼Æ¦ì¼v¹³¤¤Ãöª`°Ï¶ô¤§¬ã¨s A Study for Locating the Interested Regions in Digital Images |
2005/09~2007/06 |
ªL«Ø§» |
¥xÆW¬ì§Þ¤j¾Ç ¸ê°TºÞ²z¨t³Õ¤h¯Z |
5. |
¨Ï¥Î¦³®Ä²vªº§C¶¥¯S¼x¿ï¨ú©ó³õ´º¤ÀÃþ Scene Classification Using Efficient Low-level
Feature Selection |
2006/09~2008/07 |
³\§Ó§» |
¥xÆW¬ì§Þ¤j¾Ç ¸ê°TºÞ²z¨t³Õ¤h¯Z |
6.
|
Strategy Improvement
for Content-based Image Retrieval |
2006/09~2011/07 |
ªL©s¾W³Õ¤h |
ªA§L§Ð |
7. |
¾A¥Î©ó¶¥¼h¦¡ºô¯¸¤§¨Ï¥ÎªÌÂsÄý¦æ¬°¹w´ú¼Ò«¬ The Prediction Model of User's Browsing Behavior for Hierarchy Web Site |
2006/09~2008/07 |
³Å¬Rµ¾ |
¥æ³q¤j¾Ç ¸ê°T¤uµ{¨t³Õ¤h¯Z ¾Ç®ü±¤¯]-¤é¥»·|¬z¤j¾Ç The University of Aizu (ÂùºÓ¤h¾Ç¦ì) |
8. |
¼Æ¦ì¬Û¾÷¦Û°ÊÃn¥ú¾÷¨î¤§¬ã¨s Auto Exposure for Digital
Camera |
2006/09~2008/07 |
§d±o»¨ |
µØÄ_³q°TªÑ¥÷¦³¤½¥q |
9. |
An Image Retrieval System for Three-dimensional Trademark |
2007/09~2009/07 |
±i·¶ªâ |
°ê¥ß¥Õªe°Ó¤u±Ð¾Ç§U²z+§d»ñ§Þ³N¾Ç°|Á¿®v ¾Ç®ü¸´-¤é¥»·|¬z¤j¾Ç The University of Aizu |
10. |
A study of k-means clustering |
2007/09~2009/07 |
¼B©s®x |
¨Î¯àCanon»s«~§Þ³N³¡ |
11.
|
´Ó°ò©ó¼ç¦b»y·N¤ÀªR¤§¼v¹³³õ´º¤ÀÃþ Latent Semantic Analysis for Classifying
Scene Images |
2008/09~2010/07 |
¦¿©[¬F |
¤¸§Q²±ºë±K¾÷±ñ |
12.
|
«n°Ï¶ô¹ï¼v¹³¤ÀÃþ¼vÅT¤§¬ã¨s A Study of Influence of Important Regions in the
Image Classification |
2008/09~2012/07 |
³¯¬ü¬Â |
¹©·s¬ì§Þ |
13.
|
³Q°Ê¦¡¦Û°Ê¹ïµJ¾÷¨î¤§¬ã¨s A
Study of Passive Auto-Focus |
2009/09~2011/07 |
³\®mÞ³ |
¥æ³q¤j¾Ç ´¼¼z¥Í¬¡¬ì§Þ°Ï°ì¤¤³¡¾ã¦X¤¤¤ß(Eco-City) |
14.
|
°ÊÃn¥ú¾÷¨î¤§¬ã¨s A Study of Auto Exposure |
2009/09~2012/02 |
¬h«T·¶ |
¦°ªF¾÷±ñ |
15.
|
´Ó°ò©óÀW²v°ì¤ÀªR¼v¹³¿Ä¦X¤§¬ã¨s A Study of Image Fusion based on Frequency Domain
Analysis |
2010/09~2012/07 |
©P¬FÞ³ |
ºô»Ú´¼¼z |
16.
|
´Ó°ò©óÀW²v°ì¤ÀªR¤§¦Û°Ê¹ïµJ¾÷¨î¬ã¨s A Study of Auto-Focus based on Frequency Domain
Analysis |
2010/09~2012/07 |
¶À©v¥ |
«ä´¶¦³¤½¥q |
17.
|
´Ó°ò©óÀW²v°ì¤ÀªR¤§¦Û°Ê¹ïµJ¾÷¨î¬ã¨s An Image Retrieval System for Three-Dimensional Image |
2011/09~2013/07 |
ªLª÷¾ð |
FILA ´´¼ÖªÑ¥÷¦³¤½¥q¸ê°TºÞ²z³B |
18.
|
¥[³t«×·P´ú¾¹¿ëÃѹB°Ê«¬ºA¤§¬ã¨s Movement-type Classification by Using Acceleration |
2012/09~2014/07 |
¬h§g¿« |
^¤¥Ä_¸ê°TªÑ¥÷¦³¤½¥q(InfoPower) |
19.
|
¦h«Ãn¥ú¼v¹³¿Ä¦X¾÷¨î Multiple exposure image fusion |
2013/09~2014/07 |
ªL®a¥° |
³Ç¤h¸ê·½¾ã¦XªÑ¥÷¤½¥q |
20.
|
¤@Ó¾A¥Î©ó¼v¹³À˯Á¤§ªÅ¶¡ªí¥Üªk A Novel Spatial Representation for Image Retrieval |
2007/09~2014/07 |
³¢Åt»ö |
©ú¥x¤¤¾Ç |
21.
|
¨T¾÷¨®±Æ®ð¹L¼{¾¹ Steam Locomotive Exhaust Filter |
2013/09~201507 |
¶À«T¾§ |
ß»®æ°ª¤¤ |
22.
|
¦h«§@·~¼Ò¦¡¤U¤§¹s¤u¦¡§@·~±Æ¦¨À³¥ÎA Study of Multi-Mode Job Shop Scheduling |
201508 |
§d¹Å´ |
Xuenn Pte Ltd |
23.
|
°ªÂ¾¾Ç¥Í©ó¹q¸£³nÅéÀ³¥Î¹ê²ß½Òµ{¾Ç²ß¦æ¬°¤§¬ã¨s The Study of Computer Software Practice Course Learning Behaviors of
Student in Vocational High School |
2013/09~201602 |
¬ö©v¦ö |
©ú¥x¤¤¾Ç |
24.
|
°ÊºAÄá¼v¤§¼Ò½k¼v¹³ÁÙì¬ã¨s Deblurring process of blurred image for dynamic photography |
2013/09~2016/07 |
ªô´¼«i |
¤é¥»·|¬z¤j¾Ç The University of Aizu (ÂùºÓ¤h¾Ç¦ì) ·s¨È¬w»ö¾¹ªÑ¥÷¦³¤½¥q |
25.
|
¹B¥ÎUML¤ÀªR³]p¹ê§@ÂåÀø¸ê°T¨t²Î ¡V¥H¶E¶¡§@·~¬°¨Ò Hospital Information System Implementation Using UML - an Example of Diagnosis System |
201608 |
ÁéÂ`¦Ú |
Ä_¦¨¶°¹Î |
26.
|
°ò©ó§Ö³t³Å¥ß¸Âà´«¤§¥ßÅé¹Ï¹³¸ê®Æ®w±´°Q A Study of 3D Trademark Image Database Based on FFT 2017 |
201707 |
¿à«G¨q |
³Ó¹Ï°ê»Ú¥ø·~ªÑ¥÷¦³¤½¥q |
27.
|
¼v¹³¯S®Ä¬ÛÃö¨ç¼Æ±´°Q A study of Related Functions of Image Effects |
201712 |
ªL¶®»T |
|
28.
|
·P´ú¾¹À³¥Î©ó¼v¹³¥h¼Ò½k¤§±´°Q A study of Image Deblurring with Sensor |
201807 |
³¯Ã¢¹l |
·OÀÙÂå°| |
29.
|
¤Gºû½u©Ê¹B°Ê¥h¼Ò½k¤§±´°Q Deblurring in Two-dimensional Linear Motion |
201907 |
¨ô¥Ã®Ê |
|
30.
|
°ò©óYOLOv4®É©|ªA¸Ë°»´ú¤§¬ã¨s A Study of Fashion Apparel Detection Based on YOLOv4 |
202107 |
ªL©Ó½n |
¥ü¶Ô¬ì§Þ |
31.
|
¨Ï¥Î¨÷¿n¯«¸gºô¸ô¤ÀÃþ¿}§¿¯f«¬µøºô½¤¯fÅܲ´©³¼v¹³¤§¬ã¨s A Study of Fundus images classification for Diabetic Retinopathy using
Convolutional Neural Network |
202107 |
¬_©ÉÞ± |
¦X¶Ô§ë±± |
32.
|
ªøµu´Á°O¾Ð¼Ò«¬¹w´ú²{ª÷ªÑ§Q¤§¬ã¨s
A study of Long Short-Term Memory to Predict Cash Dividend |
202107 |
³\¨Î¬Â |
¤µºô´¼¼z |
33.
|
¨Ï¥Î¨÷¿n¯«¸gºô¸ô¤ÀÃþÄ«ªG²¢«×µ¥¯Å¤§¬ã¨s A Study of Classifying the Sweetness Level of Apples Using Convolutional Neural Networks |
202107 |
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12. ·P´ú¹B°Ê¹CÀ¸(2016.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
13. °t¦â¤j®v APP À³¥Î(2015.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
14. ¨º¦~¡B¨ºùØ¡B¨º·Ó¤ù(2014.12¸ê°T»P³q°T¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
15. «a¬R¬ì§Þ¸ê°T¨t²Î(2014.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
16. ºëÆF¶Ç»¡¿Ë¤l¤¬°Êø¥»¹CÀ¸(2014.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
17. ºÓ¯q¬ì§Þ·~¬É¹ê²ß¡X(2013.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
18. Android ¥¥xÀ³¥Î³]p¡X´Óª«¹F¤H(2012.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
19. Android ¥¥xÀ³¥Î³]p¡X¦æ°Ê¦¡°Ó¼Ð·j´M¤ÞÀº(2011.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
20. ¦h«¬d¸ß¼v¹³¸ê®Æ®w(2010.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
21. ¼v¹³³õ´º¦Û°Ê¤ÀÃþ¨t²Î(2010.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
22. ¤¬°Ê¦¡¨®¥Î½Ã¬P©w¦ì¾É¯è¨t²Î¤§³]p»P¹ê§@(2009.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
23. ¥ßÅé°Ó¼Ð·j´M¨t²Î(2009.12¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
24. ´O¤J¦¡¨t²Î¹ê§@-¥HGPS¬°¨Ò(2008.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
25. ´O¤J¦¡¨®¥Î¹q¸£¨t²Î¹ê§@(2007.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
26. ´¼¼z«¬¶¼¹¿Ô¸ß¨t²Î(2007.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
27. ¼v¹³·j´M¨t²Î(¤@) (2006.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
28. ¼v¹³·j´M¨t²Î(¤G) (2006.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
29. ºô¶³]p½Õ¦â¤j®v (2005.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
30. ºô¶¦â±m¤ÀªR(2005.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
31. »²§U±Ð¾Ç¨t²Î(2004.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
32. ¤À´²¦¡¼vµÀ£ÁY¨t²Î(¤@) (2004.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
33. ¤À´²¦¡¼vµÀ£ÁY¨t²Î(¤G) (2004.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
34. °Ó¼Ð¹Ï§Î¸ê®Æ·j´M¨t²Î(¤@) (2003.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
35. °Ó¼Ð¹Ï§Î¸ê®Æ·j´M¨t²Î(¤G) (2003.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
36. °Ó¼Ð¹Ï§Î¸ê®Æ·j´M¨t²Î(¤T) (2003.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
37. ´¼¼z«¬Ó¤H¹Ï®ÑÀ]¨t²Î(¤@) (2002.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
38. ´¼¼z«¬Ó¤H¹Ï®ÑÀ]¨t²Î(¤G) (2002.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
39. ¤å¥ó´¼¼z«¬¸ê·½¤¤¤ß(2002.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
40. ³q¥Î©Êºô¸ô°Ý¨÷(2001.5¸êºÞ¨t²¦·~¦¨ªG®i¡B¦aÂI¡G´Â¶§¬ì§Þ¤j¾Ç)
41.
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