Dumrongsak Kijdech and Supachai Vongbunyong
[1] A. Zakhama, L. Charrabi, and K. Jelassi, Intelligentselective compliance articulated robot arm robot with objectrecognition in a multi-agent manufacturing system, Interna-tional Journal of Advanced Robotic Systems, 16(2), 2019,1729881419841145. [2] D. Kirschner, R. Velik, S. Yahyanejad, M. Brandst¨otter, andM. Hofbaur, YuMi, Come and play with me! A collaborativerobot for piecing together a tangram puzzle, in A. Cham,G. Rigoll Ronzhin, and R. Meshcheryakov (eds.), Interactivecollaborative robotics, (New York: Springer InternationalPublishing, 2016), 243–251. [3] J. Liang, G. Zhang, W. Wang, Z. Hou, J. Li, X. Wang, and C.-S.Han, Dual quaternion based kinematic control for Yumi dualarm robot, Proc. 2017 14th International Conf. on UbiquitousRobots and Ambient Intelligence (URAI), 28 June–1 July 2017,2017, 114–118, doi: 10.1109/URAI.2017.7992899. [4] S.-H. Wu and X.S. Hong, Integrating computer visionand natural language instruction for collaborativerobot human-robot interaction, Proc. 2020 InternationalAutomatic Control Conf. (CACS), 4–7 Nov. 2020, 1–5,doi: 10.1109/CACS50047.2020.9289768. [5] R. Yang, T.P. Nguyen, S.H. Park, and J. Yoon, Automatedpicking-sorting system for assembling components in an IKEAchair based on the robotic vision system, InternationalJournal of Computer Integrated Manufacturing, 35(6), 2022,583–597. [6] P. Opaspilai, S. Vongbunyong, and A. Dheeravongkit,Robotic system for depalletization of pharmaceutical prod-ucts, Proc. 2021 7th International Conf. on Engineering,Applied Sciences and Technology (ICEAST), Pattaya, 2021,133–138. [7] J. Lelachaicharoeanpan and S. Vongbunyong, Classifica-tion of surgical devices with artificial neural networkapproach, Proc. 2021 7th International Conf. on Engineering,Applied Sciences and Technology (ICEAST), Pattaya, 2021,154–159. [8] Y. Wang, J. Qiu, J. Wu, and J. Wang, Inverse kinematicsolution of a 7-DOF robot with a telescopic forearmbased on joint limit and inertia matrix fluctuation, Inter-national Journal of Robotics and Automation, 38, 2023,50–59. [9] W. Fang, L. Wang, and P. Ren, Tinier-YOLO: Areal-time object detection method for constrainedenvironments, IEEE Access, 8, 2020, 1935–1944, doi:10.1109/ACCESS.2019.2961959. [10] J. Du, Understanding of object detection based on CNN familyand YOLO, Journal of Physics: Conference Series, 1004, 2018,012029, doi: 10.1088/1742-6596/1004/1/012029. [11] J. Sang, Z. Wu, P. Guo, H. Hu, H. Xiang, Q. Zhang, andB. Cai, An improved YOLOv2 for vehicle detection, Sensors,18(12), 2018, 4272. [12] J. Zhang, M. Huang, X. Jin, and X. Li, A real-time Chinesetraffic sign detection algorithm based on modified YOLOv2,Algorithms, 10(4), 2017, 127. [13] B. Benjdira, T. Khursheed, A. Koubaa, A. Ammar, andK. Ouni, Car detection using unmanned aerial vehi-cles: comparison between faster R-CNN and YOLOv3,Proc. 2019 1st International Conf. on Unmanned VehicleSystems-Oman (UVS), Muscat, 5-7 Feb. 2019, 2019, 1–6,doi: 10.1109/UVS.2019.8658300. [14] R. Girshick, Fast R-CNN, Proc. of the IEEE InternationalConf. on Computer Vision, Santiago, 2015, 1440–1448. [15] B. Tekin, S.N. Sinha, and P. Fua, Real-time seamless singleshot 6D object pose prediction, Proc. of the IEEE Conf. onComputer Vision and Pattern Recognition, Salt Lake City, UT,2018, 292–301. [16] L. Zhao and S. Li, Object detection algorithm based onimproved YOLOv3, Electronics, 9(3), 2020, 537. [17] A. Kuznetsova, T. Maleva, and V. Soloviev, Detecting applesin orchards using yolov3 and yolov5 in general and close-up images, in M. Cham, S. Qin Han, and N. Zhang (eds.),Advances in neural networks – ISNN 2020, (New York: SpringerInternational Publishing, 2020), 233–243. [18] G. Yang, W. Feng, J. Jin, Q. Lei, X. Li, G. Gui, and W.Wang, Face mask recognition system with YOLOV5 based onimage recognition, Proc. 2020 IEEE 6th International Conf.on Computer and Communications (ICCC), Chengdu, 2020,1398–1404. [19] M. Lai and L. Gao, Automatic classification of apple leafdiseases based on transfer learning, International Journal ofRobotics and Automation, 37(1), 2022, 44–51. [20] D. Dluˇznevskij, P. Stefanovic, and S. Ramanauskaite,Investigation of YOLOv5 efficiency in iPhone supportedsystems, Baltic Journal of Modern Computing, 9(3), 2021,333–344.
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