References
- L. Hungon, Defense Science & Technology Development Trend and Level vol. 1. Defense Agency for Technology and Quality: Defense Agency for Technology and Quality, 2016.
- J. Schroeder, "Future Combat Systems," DEPARTMENT OF THE ARMY WASHINGTON DC2001.
- K. Yull-Hui, C. Yong-Hoon, and K. Jin-Oh, "How to Derive the Autonomous Driving Function Level of Unmanned Ground Vehicles - Focusing on Defense Robots," The Journal of The Korean Institute of Communication Sciences, vol. 42, pp. 205-213, 1 2017. https://doi.org/10.7840/kics.2017.42.1.205
- L. Jaeyoung, L. Jongwoo, Y. Sanhyun, and K. Juhui, Military Robot vol. 1. Korea Military Academy: BooksHill, 2017.
- R. Sparrow, "Robotic weapons and the future of war," New wars and new soldiers: Military ethics in the contemporary world, pp. 117-133, 2011.
- H. Ju-Heyon, P. Sanghyuk, P. Sang-Sup, and R. Chang-Kyung, "Aiming Point Correction Technique for Ship-launched Anti-air Missiles Considering Ship Weaving Motion," Journal of Institute of Control, Robotics and Systems, vol. 20, pp. 94-100, 1 2014. https://doi.org/10.5302/J.ICROS.2014.13.1870
- J. Kyung-Hyun, K. Si-Hyun, L. Young-Cheol, and P. Byung-Suh, "An Image based Aiming Point Estimation Method for Laser Weapon System," 2015, pp. 492-493.
- M. Sonka, V. Hlavac, and R. Boyle, Image processing, analysis, and machine vision: Cengage Learning, 2014.
- J.-H. Kim, Y. Sung, and B. Y. Lattimer, "Bayesian estimation based real-time fire-heading in smoke- filled indoor environments using thermal imagery," in Robotics and Automation (ICRA), 2017 IEEE International Conference on, 2017, pp. 5231-5236.
- L. Saac and C. Jae-Soo, "Tracking and Recognition of vehicle and pedestrian for intelligent multi-visual surveillance systems," Journal of the Korea Institute of Information and Communication Engineering, vol. 19, pp. 435-442, 2 2015. https://doi.org/10.6109/jkiice.2015.19.2.435
- J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, "You only look once: Unified, real-time object detection," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 779-788.
- J. Matas, O. Chum, M. Urban, and T. Pajdla, "Robust wide-baseline stereo from maximally stable extremal regions," Image and vision computing, vol. 22, pp. 761-767, 2004. https://doi.org/10.1016/j.imavis.2004.02.006
- K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, et al., "A comparison of affine region detectors," International journal of computer vision, vol. 65, pp. 43-72, 2005. https://doi.org/10.1007/s11263-005-3848-x
- M. Fuad, M. Aqil, A. Ghani, M. Ruddin, R. Ghazali, M. F. Sulaima, et al., "A Review on Methods of Identifying and Counting Aedes Aegypti Larvae using Image Segmentation Technique," Telkomnika, vol. 15, 2017.
- C. Boutsidis, A. Zouzias, M. W. Mahoney, and P. Drineas, "Randomized dimensionality reduction for k-means clustering," IEEE Transactions on Information Theory, vol. 61, pp. 1045-1062, 2015. https://doi.org/10.1109/TIT.2014.2375327
- J. Sharadkumar and K. Suvarna, "Morphological Image Processing," International Journal in IT & Engineering, vol. 3, pp. 1-7, 2015.
-
I. Sobel, "An isotropic
$3{\pi}$ 3 image gradient operator," Machine vision for three-dimensional scenes, pp. 376-379, 1990. - J.-H. Kim and B. Y. Lattimer, "Real-time probabilistic classification of fire and smoke using thermal imagery for intelligent firefighting robot," Fire Safety Journal, vol. 72, pp. 40-49, 2015. https://doi.org/10.1016/j.firesaf.2015.02.007
- J.-H. Kim, S. Jo, and B. Y. Lattimer, "Feature Selection for Intelligent Firefighting Robot Classification of Fire, Smoke, and Thermal Reflections Using Thermal Infrared Images," Journal of Sensors, vol. 2016, p. 13, 2016.