| 1 |
Ministry of Culture, Sports and Tourism. http://www.korea.kr/news/pressReleaseView.do? newsId=156366736 |
미소장 |
| 2 |
Korea Agency for Infrastructure Technology Advancement. https://www.kaia.re.kr/portal/landmark/readTskVi ew.do?tskId=113086&yearCnt=4&cate1=&cate2=&cate3=&year=&bizName=&psnNm=&orgNm =&tskName=%EC%B0%A8%EB%9F%89%20ICT %EA%B8%B0%EB%B0%98%20%EA%B8%B4%E A%B8%89%EA%B5%AC%EB%82%9C%EC%B2%B4%EA%B3%84%20%EA%B5%AC%EC%B6%95%20%EC%97%B0%EA%B5%AC&sort=&pageIn dex=1&menuNo=200060#none |
미소장 |
| 3 |
Support-vector networks  |
미소장 |
| 4 |
Training Invariant Support Vector Machines  |
미소장 |
| 5 |
S. Pradhan, W. Ward, K. Hacioglu, J. H. Martin, D. Jurafsky(2004), “Shallow semantic parsing using support vector machines.” In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004, pp. 233-240. |
미소장 |
| 6 |
Achanta, Radhakrishna, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Süsstrunk. Slic superpixels. No. REP_WORK. 2010. |
미소장 |
| 7 |
Tri-training: exploiting unlabeled data using three classifiers  |
미소장 |
| 8 |
I. Arel, C. Liu, T. Urbanik, A. G. Kohls(2005), “Reinforcement learning-based multi-agent system for network traffic signal control.” IET Intelligent Transport Systems, 4(2):128-135. |
미소장 |
| 9 |
A. Graves, A. Mohamed, G. Hinton(2013), “Speech recognition with deep recurrent neural networks.”In 2013 IEEE international conference on acoustics, speech and signal processing, pp. 6645-6649. |
미소장 |
| 10 |
H. Hewamalage, C. Bergmeir, K. Bandara(2019), “Recurrent neural networks for time series forecasting: Current status and future directions.”arXiv preprint, arXiv:1909.00590 |
미소장 |
| 11 |
M. Baccouche, F. Mamalet, C. Wolf, C. Garcia, A. Baskurt(2011), “Sequential deep learning for human action recognition.” In International workshop on human behavior understanding, pp. 29-39. Springer, Berlin, Heidelberg. |
미소장 |
| 12 |
Comma.ai, https://comma.ai/ |
미소장 |
| 13 |
Drive.ai, http://www.drive.ai/ |
미소장 |
| 14 |
Autox, https://www.autox.ai/ |
미소장 |
| 15 |
ADAS One, http://adasone.com/ |
미소장 |
| 16 |
LG Economic Research Institute. http://www.lgeri.com/uploadFiles/ko/pdf/busi/LG ERI_Report_20171122_20170322130355595.pdf |
미소장 |
| 17 |
National Emergency Medical Center. https://www.e-gen.or.kr/nemc/investigation_vie w.do?brdctsno=142&upperfixyn=N¤tPag eNum=3&brdclscd=&searchTarget=ALL&sear chKeyword=&searchDatayear= |
미소장 |
| 18 |
Korea Agency for Infrastructure Technology Advancement. https://www.kaia.re.kr/portal/landmark/readTsk View.do?menuNo=200060&tskId=113086&year Cnt=1. |
미소장 |
| 19 |
M. Sammarco, M. Detyniecki(2018), “Crashzam:Sound-based Car Crash Detection.” In VEHITS, pp. 27-35. |
미소장 |
| 20 |
P. Amrith, E. Umamaheswari, R. U. Anitha, D. Mani, D. M. Ajay(2019), Smart Detection of Vehicle Accidents using Object Identification Sensors with Artificial Intelligent Systems. |
미소장 |
| 21 |
CrashCather. https://github.com/rwk506/CrashCatcher |
미소장 |
| 22 |
V. E. M. Arceda, E. L. Riveros(2018), “Fast car crash detection in video.” In 2018 XLIV Latin American Computer Conference (CLEI), pp. 632-637. |
미소장 |