|
[1] About Epson Robots, Available online: URL: https://epson.com/about-robots(accessed on 29, 12, 2021)
[2] IFR forecast: 1.7 million new robots to transform the world´s factories, Available online: URL: https://ifr.org/ifr-press-releases/news/ifr-forecast-1.7-million-new-robots-to-transform-the-worlds-factories-by-20, (accessed on 27,09,2017).
[3] Preventing the Injury of Workers by Robots, Available online: URL: https://www.cdc.gov/niosh/docs/85-103/, (accessed on 06,06,2014)
[4] ROBOTICS-The Problem, Available online: URL: https://www.cdc.gov/niosh/topics/robotics/aboutthecenter.html, (accessed on 07,12,2020)
[5] 勞動部職業安全衛生署，中華民國 109 年勞動檢查統計年報，可獲取網址 URL: https://www.osha.gov.tw/1106/1164/1165/1168/34345/, (可訪問日期 18,08,2021).
[6] Hubel D. H. & Wisel T. N. (1961). Receptive Fields, Binocular Interaction And Functional Architecture In The Cat's Visual Cortex. Neurophysiolojy Laboratory, Department of Pharmacology Harvard Aledical School, Boston, Massachusetts, U.S.A.
[7] Yann L. C., Patrick H., Leon B., & Yoshua B. (1989). Object Recognition with Gradient-Based Learning, AT&T Shannon Lab, U.S.A.
[8] Imoto, K., Nakai, T., Ike, T., Haruki, K., & Sato, Y. (2018, December). A CNN-based transfer learning method for defect classification in semiconductor manufacturing. In 2018 international symposium on semiconductor manufacturing (ISSM) (pp. 1-3). IEEE
[9] Narvekar, C., & Rao, M. (2020, 3-5 Dec. 2020). Flower classification using CNN and transfer learning in CNN- Agriculture Perspective. Paper presented at the 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS).
[10] Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You only look once: Unified, real-time object detection. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 779-788).
[11] Bochkovskiy, A., Wang, C. Y., & Liao, H. Y. M. (2020). Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934.
[12] Wang, C. Y., Bochkovskiy, A., & Liao, H. Y. M. (2021). Scaled-yolov4: Scaling cross stage partial network. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 13029-13038)
[13] Jiang, Z., Zhao, L., Li, S., & Jia, Y. (2020). Real-time object detection method based on improved YOLOv4-tiny. arXiv preprint arXiv:2011.04244.
[14] Dewi, C., Chen, R. C., Liu, Y. T., Jiang, X., & Hartomo, K. D. (2021). Yolo V4 for advanced traffic sign recognition with synthetic training data generated by various GAN. IEEE Access, 9, 97228-97242.
[15] Mamdouh, N., & Khattab, A. (2021). YOLO-Based Deep Learning Framework for Olive Fruit Fly Detection and Counting. IEEE Access.
[16] Xu, Z., Li, J., & Zhang, M. (2021). A Surveillance Video Real-Time Analysis System Based on Edge-Cloud and FL-YOLO Cooperation in Coal Mine. IEEE Access, 9, 68482-68497.
[17] GL-R系列安全光柵， KEYENCE，可獲取網址 URL: https://www.keyence.com.tw/products/safety/light-curtain/gl- (可訪問日期
28,12,2021).
[18] GS 系列安全門感測器， KEYENCE，可獲取網址 URL: https://www.keyence.com.tw/products/safety/safety-interlock-switches/ (可訪問日
期 28,12,2021).
50
[19] F3SJ安全光柵， OMRON，可獲取網址 URL: https://www.omron.com.tw/products/family/1581/, (可訪問日期 30,12,2021).
[20] Safety Light Curtains, BANNER, Available online: URL: https://www.bannerengineering.com/us/en/products/machine-safety/safety-light-curtains.html#all, (accessed on 30,12,2021)
[21] YOLOv4 vs YOLOv4-tiny, Techzizou, https://medium.com/analytics-vidhya/yolov4-vs-yolov4-tiny-97932b6ec8ec, (accessed on 25,02,2021)
[22] 進階人工智慧嵌入式系統， NVIDIA，可獲取網址 URL: https://www.nvidia.com/zh-tw/autonomous-machines/embedded-systems/, (可訪問日期 30,12,2021)
[23] NVIDIA TensorRT可编程推理加速器進階人工智慧嵌入式系統， NVIDIA，可獲取
網址 URL: https://developer.nvidia.cn/zh-cn/tensorrt, (可訪問日期 30,12,2021)
[24] KR 10 R1100-2 KUKA，可獲取網址 URL: https://media.digikey.com/pdf/Data%20Sheets/KUKA%20Robotics%20PDFs/KR_10_R1100-2.pdf (可訪問日期 30,12,2021)
[25] DELTA DVP-12SE PLC DELTA，可獲取網址 URL: https://www.deltaww.com/zh-TW/products/PLC-Programmable-Logic-Controllers/272, (可訪問日期 30,12,2021)
|