{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T18:23:27Z","timestamp":1748543007901,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819964796"},{"type":"electronic","value":"9789819964802"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-6480-2_50","type":"book-chapter","created":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T09:02:09Z","timestamp":1696496529000},"page":"608-618","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["MLP Neural Network-Based Precise Localization of Robot Assembly Parts"],"prefix":"10.1007","author":[{"given":"Bin","family":"Cheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zonggang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjun","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanglin","family":"An","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,6]]},"reference":[{"key":"50_CR1","doi-asserted-by":"publisher","first-page":"101965","DOI":"10.1016\/j.rcim.2020.101965","volume":"65","author":"S Pagano","year":"2020","unstructured":"Pagano, S., Russo, R., Savino, S.: A vision guided robotic system for flexible gluing process in the footwear industry. Robot. Comput. Integr. Manuf. 65, 101965 (2020)","journal-title":"Robot. Comput. Integr. Manuf."},{"issue":"4","key":"50_CR2","doi-asserted-by":"publisher","first-page":"2251","DOI":"10.1109\/TRO.2022.3142671","volume":"38","author":"S Zhuang","year":"2022","unstructured":"Zhuang, S., Dai, C., Shan, G., et al.: Robotic rotational positioning of end effectors for micromanipulation. IEEE Trans. Robot. 38(4), 2251\u20132261 (2022)","journal-title":"IEEE Trans. Robot."},{"issue":"9","key":"50_CR3","doi-asserted-by":"publisher","first-page":"10032","DOI":"10.1109\/JSEN.2023.3258899","volume":"23","author":"A Gilmour","year":"2023","unstructured":"Gilmour, A., Jackson, W., Zhang, D., et al.: Robotic positioning for quality assurance of feature sparse components using a depth-sensing camera. IEEE Sens. J. 23(9), 10032\u201310040 (2023)","journal-title":"IEEE Sens. J."},{"issue":"2","key":"50_CR4","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1007\/s12008-022-01077-8","volume":"17","author":"VD Cong","year":"2023","unstructured":"Cong, V.D.: Visual servoing control of 4-DOF palletizing robotic arm for vision based sorting robot system. Int. J. Interact. Des. Manuf. 17(2), 717\u2013728 (2023)","journal-title":"Int. J. Interact. Des. Manuf."},{"issue":"3","key":"50_CR5","doi-asserted-by":"publisher","first-page":"5728","DOI":"10.1109\/LRA.2021.3084885","volume":"6","author":"X Xu","year":"2021","unstructured":"Xu, X., Tang, R., Gong, L., Chen, B., Zuo, S.: Two dimensional position-based visual servoing for soft tissue endomicroscopy. IEEE Robot. Autom. Lett. 6(3), 5728\u20135735 (2021). https:\/\/doi.org\/10.1109\/LRA.2021.3084885","journal-title":"IEEE Robot. Autom. Lett."},{"issue":"5","key":"50_CR6","first-page":"2583","volume":"53","author":"G Rotithor","year":"2023","unstructured":"Rotithor, G., Salehi, I., Tunstel, E., et al.: Stitching dynamic movement primitives and image-based visual servo control. IEEE Trans. Syst. 53(5), 2583\u20132593 (2023)","journal-title":"IEEE Trans. Syst."},{"issue":"7","key":"50_CR7","doi-asserted-by":"publisher","first-page":"3993","DOI":"10.1016\/j.jfranklin.2020.01.012","volume":"357","author":"JX Dong","year":"2020","unstructured":"Dong, J.X., Zhang, J.: A new image-based visual servoing method with velocity direction control. J. Franklin Inst. 357(7), 3993\u20134007 (2020). https:\/\/doi.org\/10.1016\/j.jfranklin.2020.01.012","journal-title":"J. Franklin Inst."},{"issue":"8","key":"50_CR8","doi-asserted-by":"publisher","first-page":"903","DOI":"10.3390\/electronics8080903","volume":"8","author":"A Ghasemi","year":"2019","unstructured":"Ghasemi, A., Li, P., Xie, W.-F., Tian, W.: Enhanced switch image-based visual servoing dealing with features loss. Electronics 8(8), 903 (2019). https:\/\/doi.org\/10.3390\/electronics8080903","journal-title":"Electronics"},{"issue":"4","key":"50_CR9","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1049\/cth2.12238","volume":"16","author":"Z Qiu","year":"2022","unstructured":"Qiu, Z., Wu, Z.: Adaptive neural network control for image-based visual servoing of robot manipulators. IET Control Theory Appl. 16(4), 443\u2013453 (2022)","journal-title":"IET Control Theory Appl."},{"key":"50_CR10","doi-asserted-by":"publisher","first-page":"103669","DOI":"10.1109\/ACCESS.2022.3203734","volume":"10","author":"Z Arif","year":"2022","unstructured":"Arif, Z., Fu, Y., Siddiqui, M.K., Zhang, F.: Visual error constraint free visual servoing using novel switched part Jacobian control. IEEE Access 10, 103669\u2013103693 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3203734","journal-title":"IEEE Access"},{"key":"50_CR11","doi-asserted-by":"crossref","unstructured":"Bateux, Q., Marchand, E., Leitner, J., et al.: Training deep neural networks for visual servoing. In: IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia, pp. 3307\u20133314 (2018)","DOI":"10.1109\/ICRA.2018.8461068"},{"issue":"4","key":"50_CR12","doi-asserted-by":"publisher","first-page":"3251","DOI":"10.3233\/JIFS-211116","volume":"42","author":"Z Xuejian","year":"2022","unstructured":"Xuejian, Z., Xiaobing, H., Hang, L.: A speed inference planning of groove cutting robot based on machine vision and improved fuzzy neural network. J. Intell. Fuzzy Syst. 42(4), 3251\u20133264 (2022)","journal-title":"J. Intell. Fuzzy Syst."},{"key":"50_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2022.3229248","volume":"71","author":"S Yan","year":"2022","unstructured":"Yan, S., Tao, X., Xu, D.: Image-based visual servoing system for components alignment using point and line features. IEEE Trans. Instrum. Meas. 71, 1\u201311 (2022)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"50_CR14","unstructured":"Popescu, M.C., Balas, V., Perescu-Popescu, L.: Multilayer perceptron and neural net-works. WSEAS Transactions on Circuits and Systems 8 (2009)"},{"key":"50_CR15","unstructured":"Tolstikhin, I., Houlsby, N., Kolesnikov, A., et al.: MLP-Mixer: an all-MLP architecture for vision. In: Neural Information Processing Systems (2021)"},{"key":"50_CR16","doi-asserted-by":"crossref","unstructured":"Yang, L.F., Li, X., Song, R.J., et al.: Dynamic MLP for fine-grained image classification by leveraging geographical and temporal information. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, LA, USA, pp. 10935\u201310944 (2022)","DOI":"10.1109\/CVPR52688.2022.01067"},{"key":"50_CR17","unstructured":"Lv, T.X., Bai, C.Y., Wang, C.J.: MDMLP: Image Classification from Scratch on Small Datasets with MLP. AtXir abs\/2205.14477 (2022)"},{"key":"50_CR18","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., et al.: ORB: an efficient alternative to SIFT or SURF. In: 2011 International Conference on Computer Vision, Barcelona, Spain, pp. 2564\u20132571 (2011)","DOI":"10.1109\/ICCV.2011.6126544"},{"issue":"3","key":"50_CR19","doi-asserted-by":"publisher","first-page":"2603","DOI":"10.1109\/JSEN.2021.3138846","volume":"22","author":"C Sun","year":"2022","unstructured":"Sun, C., Wu, X., Sun, J., et al.: Multi-stage refinement feature matching using adaptive ORB features for robotic vision navigation. IEEE Sens. J. 22(3), 2603\u20132617 (2022)","journal-title":"IEEE Sens. J."},{"key":"50_CR20","doi-asserted-by":"publisher","first-page":"117365","DOI":"10.1109\/ACCESS.2020.3004284","volume":"8","author":"Q Chen","year":"2020","unstructured":"Chen, Q., Zhang, W., Lou, Y.: Forecasting stock prices using a hybrid deep learning model integrating attention mechanism, multi-layer perceptron, and bidirectional long-short term memory neural network. IEEE Access 8, 117365\u2013117376 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.3004284","journal-title":"IEEE Access"},{"issue":"5","key":"50_CR21","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1016\/j.robot.2009.11.003","volume":"58","author":"O Tahri","year":"2010","unstructured":"Tahri, O., Mezouar, Y.: On visual servoing based on efficient second order minimization. Robot. Auton. Syst. 58(5), 712\u2013719 (2010). https:\/\/doi.org\/10.1016\/j.robot.2009.11.003","journal-title":"Robot. Auton. Syst."}],"container-title":["Lecture Notes in Computer Science","Intelligent Robotics and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-6480-2_50","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T09:08:19Z","timestamp":1696496899000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-6480-2_50"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819964796","9789819964802"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-6480-2_50","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"6 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Robotics and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hangzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icira2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icira2023.org\/","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":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"630","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":"431","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":"0","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":"68% - 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":"2","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":"2","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)"}}]}}