{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T20:44:15Z","timestamp":1743021855584,"version":"3.40.3"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031203978"},{"type":"electronic","value":"9783031203985"}],"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\/978-3-031-20398-5_8","type":"book-chapter","created":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T09:12:17Z","timestamp":1669367537000},"page":"98-110","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Design and Implementation of Distributed Image Recognition App with Federal Learning Techniques"],"prefix":"10.1007","author":[{"given":"Yu-Wei","family":"Chan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo-You","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi-Ming","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao-Tung","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,26]]},"reference":[{"key":"8_CR1","doi-asserted-by":"crossref","unstructured":"Mohassel, P., Zhang, Y.: Secureml: A system for scalable privacy-preserving machine learning. Proc. of the 2017 IEEE symposium on security and privacy (May 2017)","DOI":"10.1109\/SP.2017.12"},{"key":"8_CR2","doi-asserted-by":"crossref","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553) (2015)","DOI":"10.1038\/nature14539"},{"key":"8_CR3","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proc. of the IEEE conference on computer vision and pattern recognition (CVPR) (June 2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"8_CR4","doi-asserted-by":"crossref","unstructured":"Cao, Z., Hidalgo, G., Simon, T., Wei, S.-E., Sheikh, Y.: OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields. In: IEEE Transactions on Pattern Analysis and Machine Intelligence 43(1), pp. 172\u2013186 (1 Jan. 2021)","DOI":"10.1109\/TPAMI.2019.2929257"},{"key":"8_CR5","doi-asserted-by":"crossref","unstructured":"Xiong, W., Wu, L., Alleva, F., Droppo, J., Huang, X., Stolcke, A.: The Microsoft 2017 conversational speech recognition system. In: Proc. of 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (April 2018)","DOI":"10.1109\/ICASSP.2018.8461870"},{"issue":"3","key":"8_CR6","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/MCI.2018.2840738","volume":"13","author":"T Young","year":"2018","unstructured":"Young, T., Hazarika, D., Poria, S., Cambria, E.: Recent trends in deep learning based natural language processing. IEEE Comput. Intell. Mag. 13(3), 55\u201375 (2018)","journal-title":"IEEE Comput. Intell. Mag."},{"issue":"4","key":"8_CR7","doi-asserted-by":"publisher","first-page":"2595","DOI":"10.1109\/COMST.2018.2846401","volume":"20","author":"M Qian","year":"2018","unstructured":"Qian, M., Fei, H., Hao, Q.: Deep learning for intelligent wireless networks: a comprehensive survey. IEEE Communications Surveys & Tutorials 20(4), 2595\u20132621 (2018)","journal-title":"IEEE Communications Surveys & Tutorials"},{"key":"8_CR8","unstructured":"Kone\u010dn\u00fd, J., McMahan, H.B., Yu, F.X., Richt\u00e1rik, P., Suresh, A.T., Bacon, D.: Federated learning: Strategies for improving communication efficiency (2016). arXiv preprint arXiv:1610.05492"},{"issue":"2","key":"8_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3298981","volume":"10","author":"Q Yang","year":"2019","unstructured":"Yang, Q., Liu, Y., Chen, T., Tong, Y.: Federated machine learning: concept and applications. ACM Trans. Intell. Sys. Technol. (TIST) 10(2), 1\u201319 (2019)","journal-title":"ACM Trans. Intell. Sys. Technol. (TIST)"},{"key":"8_CR10","unstructured":"Bonawitz, K., et al.: Towards federated learning at scale: System design (2019). arXiv preprint arXiv:1902.01046"},{"key":"8_CR11","doi-asserted-by":"crossref","unstructured":"Albawi, S., Mohammed, T.A., Al-Zawi, S.: Understanding of a convolutional neural network. In: Proc. of 2017 International Conference on Engineering and Technology (ICET) (Aug. 2017)","DOI":"10.1109\/ICEngTechnol.2017.8308186"},{"key":"8_CR12","unstructured":"The CIFAR-10 dataset https:\/\/www.cs.toronto.edu\/~kriz\/cifar.html"},{"key":"8_CR13","unstructured":"Visualization - Deeplearning4j, https:\/\/deeplearning4j.konduit.ai\/tuning-and-training\/visualization"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Smart Grid and Internet of Things"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20398-5_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T09:36:57Z","timestamp":1669369017000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20398-5_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031203978","9783031203985"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20398-5_8","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"26 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SGIoT","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Smart Grid and Internet of Things","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sgiot2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sgiot.eai-conferences.org\/2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Confy+","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"57","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"9","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"16% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}