{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T06:40:25Z","timestamp":1742971225888,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030959029"},{"type":"electronic","value":"9783030959036"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-95903-6_32","type":"book-chapter","created":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T13:03:32Z","timestamp":1643720612000},"page":"301-307","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A Soldering Motion Analysis System for\u00a0Danger Detection Considering Object Detection and\u00a0Attitude Estimation"],"prefix":"10.1007","author":[{"given":"Tomoya","family":"Yasunaga","sequence":"first","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Tetsuya","family":"Oda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Nobuki","family":"Saito","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Aoto","family":"Hirata","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Chihiro","family":"Yukawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Yuki","family":"Nagai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]},{"given":"Masaharu","family":"Hirota","sequence":"additional","affiliation":[],"role":[{"role":"author","vocab":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,2,2]]},"reference":[{"key":"32_CR1","doi-asserted-by":"crossref","unstructured":"Yasunaga, T., et al.: Object detection and pose estimation approaches for soldering danger detection. In: Proceedings of the IEEE 10-th Global Conference on Consumer Electronics, pp. 776\u2013777 (2021)","DOI":"10.1109\/GCCE53005.2021.9621849"},{"key":"32_CR2","doi-asserted-by":"crossref","unstructured":"Toyoshima, K., et al.: Proposal of a haptics and LSTM based soldering motion analysis system. In: Proceedings of the IEEE 10-th Global Conference on Consumer Electronics, pp. 1\u20132 (2021)","DOI":"10.1109\/GCCE53005.2021.9621916"},{"key":"32_CR3","series-title":"Lecture Notes in Networks and Systems","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1007\/978-3-030-61108-8_44","volume-title":"Advances on Broad-Band Wireless Computing, Communication and Applications","author":"Y Hirota","year":"2021","unstructured":"Hirota, Y., Oda, T., Saito, N., Hirata, A., Hirota, M., Katatama, K.: Proposal and experimental results of an ambient intelligence for training on soldering iron holding. In: Barolli, L., Takizawa, M., Enokido, T., Chen, H.-C., Matsuo, K. (eds.) BWCCA 2020. LNNS, vol. 159, pp. 444\u2013453. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-61108-8_44"},{"issue":"2","key":"32_CR4","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1504\/IJWGS.2017.083384","volume":"13","author":"T Oda","year":"2017","unstructured":"Oda, T., et al.: Design and implementation of an iot-based e-learning testbed. Int. J. Web Grid Serv. 13(2), 228\u2013241 (2017)","journal-title":"Int. J. Web Grid Serv."},{"issue":"3","key":"32_CR5","first-page":"312","volume":"19","author":"Y Liu","year":"2017","unstructured":"Liu, Y., et al.: Design and implementation of testbed using IoT and P2P technologies: improving reliability by a fuzzy-based approach. Int. J. Commun. Netw. Distrib. Syst. 19(3), 312\u2013337 (2017)","journal-title":"Int. J. Commun. Netw. Distrib. Syst."},{"key":"32_CR6","unstructured":"Papageorgiou, C., et al.: A general framework for object detection. In: Proceedings of the IEEE 6th International Conference on Computer Vision, pp. 555\u2013562 (1998)"},{"issue":"9","key":"32_CR7","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1109\/TPAMI.2009.167","volume":"32","author":"P Felzenszwalb","year":"2009","unstructured":"Felzenszwalb, P., et al.: Object detection with discriminatively trained part-based models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1627\u20131645 (2009)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"32_CR8","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1504\/IJSSC.2017.084119","volume":"7","author":"R Obukata","year":"2017","unstructured":"Obukata, R., et al.: Design and evaluation of an ambient intelligence testbed for improving quality of life. Int. J. Space-Based Situated Comput. 7(1), 8\u201315 (2017)","journal-title":"Int. J. Space-Based Situated Comput."},{"key":"32_CR9","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1007\/978-3-030-15035-8_34","volume-title":"Web, Artificial Intelligence and Network Applications","author":"T Oda","year":"2019","unstructured":"Oda, T., Ueda, C., Ozaki, R., Katayama, K.: Design of a deep q-network based simulation system for actuation decision in ambient intelligence. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds.) WAINA 2019. AISC, vol. 927, pp. 362\u2013370. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-15035-8_34"},{"key":"32_CR10","series-title":"Lecture Notes on Data Engineering and Communications Technologies","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1007\/978-3-319-49106-6_61","volume-title":"Advances on Broad-Band Wireless Computing, Communication and Applications","author":"R Obukata","year":"2017","unstructured":"Obukata, R., Oda, T., Elmazi, D., Ikeda, M., Barolli, L.: Performance evaluation of an ami testbed for improving qol: evaluation using clustering approach considering parallel processing. In: BWCCA 2016. LNDECT, vol. 2, pp. 623\u2013630. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-49106-6_61"},{"issue":"1","key":"32_CR11","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1108\/IJWIS-12-2016-0072","volume":"13","author":"M Yamada","year":"2017","unstructured":"Yamada, M., et al.: Evaluation of an iot-based e-learning testbed: performance of olsr protocol in a nlos environment and mean-shift clustering approach considering electroencephalogram data. Int. J. Web Inf. Syst. 13(1), 2\u201313 (2017)","journal-title":"Int. J. Web Inf. Syst."},{"key":"32_CR12","doi-asserted-by":"crossref","unstructured":"Toshev, A., Szegedy, C.: DeepPose: human pose estimation via deep neural networks. In: Proceedings of the 27-th IEEE\/CVF Conference on Computer Vision and Pattern Recognition (IEEE\/CVF CVPR-2014), pp. 1653\u20131660 (2014)","DOI":"10.1109\/CVPR.2014.214"},{"issue":"6","key":"32_CR13","first-page":"1426","volume":"19","author":"R Haralick","year":"1989","unstructured":"Haralick, R., et al.: Pose estimation from corresponding point data. IEEE Trans. Syst. 19(6), 1426\u20131446 (1989)","journal-title":"IEEE Trans. Syst."},{"key":"32_CR14","doi-asserted-by":"crossref","unstructured":"Fang, H., et al.: Rmpe: regional multi-person pose estimation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2334\u20132343 (2017)","DOI":"10.1109\/ICCV.2017.256"},{"key":"32_CR15","doi-asserted-by":"crossref","unstructured":"Xiao, B., et al.: Simple baselines for human pose estimation and tracking. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 466\u2013481 (2018)","DOI":"10.1007\/978-3-030-01231-1_29"},{"key":"32_CR16","doi-asserted-by":"crossref","unstructured":"Martinez, J., et al.: A simple yet effective baseline for 3d human pose estimation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2640\u20132649 (2017)","DOI":"10.1109\/ICCV.2017.288"},{"key":"32_CR17","unstructured":"Zhang, F., et al.: MediaPipe Hands: On-device Real-time Hand Tracking, arXiv preprint arXiv:2006.10214 (2020)"},{"key":"32_CR18","doi-asserted-by":"crossref","unstructured":"Shin, J., et al.: American sign language alphabet recognition by extracting feature from hand pose estimation. Sensors (2021)","DOI":"10.3390\/s21175856"},{"key":"32_CR19","unstructured":"Hirota, Y., et al.: Proposal and experimental results of a DNN based real-time recognition method for ohsone style fingerspelling in static characters environment. In: Proceedings of the IEEE 9-th Global Conference on Consumer Electronics"},{"key":"32_CR20","doi-asserted-by":"crossref","unstructured":"Erol, A., et al.: Vision-based hand pose estimation: a review. Comput. Vis. Image Underst. 52\u201373 (2007)","DOI":"10.1016\/j.cviu.2006.10.012"},{"key":"32_CR21","unstructured":"Abolmaali, S., et al.: Pill ingestion action recognition using mediapipe holistic to monitor elderly patients. Int. Supply Chain Technol. J. 7(11) (2021)"},{"key":"32_CR22","doi-asserted-by":"crossref","unstructured":"Redmon, J., et al.: You only look once: unified, real-time object detection. In: Proceedings of the 29-th IEEE\/CVF Conference on Computer Vision and Pattern Recognition (IEEE\/CVF CVPR-2016), pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"32_CR23","doi-asserted-by":"crossref","unstructured":"Zhou, F., et al.: Safety helmet detection based on YOLOv5. In: Proceedings of the IEEE International Conference on Power Electronics, Computer Applications (ICPECA), pp. 6\u201311 (2021)","DOI":"10.1109\/ICPECA51329.2021.9362711"},{"key":"32_CR24","doi-asserted-by":"crossref","unstructured":"Yu-Chuan, B., et al.: Using improved YOLOv5s for defect detection of thermistor wire solder joints based on infrared thermography. In: Proceedings of the 5th International Conference on Automation, Control and Robots (ICACR), pp. 29\u201332 (2021)","DOI":"10.1109\/ICACR53472.2021.9605165"},{"key":"32_CR25","unstructured":"Lugaresi, C., et al.: MediaPipe: A Framework for Building Perception Pipelines, arXiv preprint arXiv:1906.08172 (2019)"}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Advances in Internet, Data &amp; Web Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-95903-6_32","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T18:32:29Z","timestamp":1726597949000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-95903-6_32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030959029","9783030959036"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-95903-6_32","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"2 February 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EIDWT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Emerging Internetworking, Data & Web Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Okayama","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 February 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 February 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eidwt2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}