{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T14:55:51Z","timestamp":1743087351626,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031441974"},{"type":"electronic","value":"9783031441981"}],"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\/978-3-031-44198-1_3","type":"book-chapter","created":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T08:02:34Z","timestamp":1695283354000},"page":"26-37","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Global Feature Fusion Network for\u00a0Lettuce Growth Trait Detection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7957-0441","authenticated-orcid":false,"given":"Zhengxian","family":"Wu","sequence":"first","affiliation":[]},{"given":"Jiaxuan","family":"Wu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6500-3868","authenticated-orcid":false,"given":"Yiming","family":"Xue","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4199-2988","authenticated-orcid":false,"given":"Juan","family":"Wen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1515-3475","authenticated-orcid":false,"given":"Ping","family":"Zhong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,22]]},"reference":[{"key":"3_CR1","doi-asserted-by":"crossref","unstructured":"Kim, M.J., Moon, Y., Tou, J.C., Mou, B., Waterland, N.L.: Nutritional value, bioactive compounds and health benefits of lettuce (Lactuca sativa L.). J. Food Compos. Anal. 49, 19\u201334 (2016)","DOI":"10.1016\/j.jfca.2016.03.004"},{"key":"3_CR2","unstructured":"Wells, H.F., Bentley, J., et al.: Dietary assessment of us vegetable and dry pulse crops sector-updated1. Electronic Outlook Report from the Economic Research Service (VGS-357-SA1) (2016)"},{"key":"3_CR3","doi-asserted-by":"publisher","unstructured":"Schmilewski, G.: Growing medium constituents used in the EU. In: International Symposium on Growing Media 2007 819, pp. 33\u201346 (2007). https:\/\/doi.org\/10.17660\/ActaHortic.2009.819.3","DOI":"10.17660\/ActaHortic.2009.819.3"},{"issue":"8","key":"3_CR4","doi-asserted-by":"publisher","first-page":"538","DOI":"10.1016\/j.jssas.2020.10.002","volume":"19","author":"VM R\u00edos","year":"2020","unstructured":"R\u00edos, V.M., Gmez Herrera, M.D., Sugita, N.H., Alayn Luaces, P.: Water status response of pineapple using destructive and non-destructive indicators and their relations in two contrasting seasons. J. Saudi Soc. Agric. Sci. 19(8), 538\u2013547 (2020). https:\/\/doi.org\/10.1016\/j.jssas.2020.10.002","journal-title":"J. Saudi Soc. Agric. Sci."},{"key":"3_CR5","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.biosystemseng.2013.08.011","volume":"117","author":"YHF Yeh","year":"2014","unstructured":"Yeh, Y.H.F., Lai, T.C., Liu, T.Y., Liu, C.C., Chung, W.C., Lin, T.T.: An automated growth measurement system for leafy vegetables. Biosyst. Eng. 117, 43\u201350 (2014)","journal-title":"Biosyst. Eng."},{"issue":"1","key":"3_CR6","doi-asserted-by":"publisher","first-page":"89","DOI":"10.5307\/JBE.2015.40.1.089","volume":"40","author":"DH Jung","year":"2015","unstructured":"Jung, D.H., Park, S.H., Han, X.Z., Kim, H.J.: Image processing methods for measurement of lettuce fresh weight. J. Biosyst. Eng. 40(1), 89\u201393 (2015). https:\/\/doi.org\/10.5307\/JBE.2015.40.1.089","journal-title":"J. Biosyst. Eng."},{"key":"3_CR7","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/j.compag.2018.09.010","volume":"154","author":"AK Mortensen","year":"2018","unstructured":"Mortensen, A.K., et al.: Segmentation of lettuce in coloured 3d point clouds for fresh weight estimation. Comput. Electr. Agric. 154, 373\u2013381 (2018). https:\/\/doi.org\/10.1016\/j.compag.2018.09.010","journal-title":"Comput. Electr. Agric."},{"key":"3_CR8","doi-asserted-by":"publisher","first-page":"105827","DOI":"10.1016\/j.compag.2020.105827","volume":"179","author":"A Reyes-Yanes","year":"2020","unstructured":"Reyes-Yanes, A., Martinez, P., Ahmad, R.: Real-time growth rate and fresh weight estimation for little gem romaine lettuce in aquaponic grow beds. Comput. Electr. Agric. 179, 105827 (2020). https:\/\/doi.org\/10.1016\/j.compag.2020.105827","journal-title":"Comput. Electr. Agric."},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Jmour, N., Zayen, S., Abdelkrim, A.: Convolutional neural networks for image classification. In: 2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), pp. 397\u2013402. IEEE (2018)","DOI":"10.1109\/ASET.2018.8379889"},{"key":"3_CR10","doi-asserted-by":"publisher","unstructured":"Qu, Z., Jin, H., Zhou, Y., Yang, Z., Zhang, W.: Focus on local: detecting lane marker from bottom up via key point. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021, pp. 14117\u201314125 (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.01390","DOI":"10.1109\/CVPR46437.2021.01390"},{"key":"3_CR11","doi-asserted-by":"publisher","unstructured":"An, X., et al.: Killing two birds with one stone: efficient and robust training of face recognition CNNs by partial FC. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), pp. 4032\u20134041 (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.00401","DOI":"10.1109\/CVPR52688.2022.00401"},{"key":"3_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1007\/978-3-031-15937-4_64","volume-title":"Artificial Neural Networks and Machine Learning - ICANN 2022","author":"Y Yang","year":"2022","unstructured":"Yang, Y.: SDCN: a species-disease hybrid convolutional neural network for plant disease recognition. In: Pimenidis, E., Angelov, P., Jayne, C., Papaleonidas, A., Aydin, M. (eds.) ICANN 2022. LNCS, vol. 13532, pp. 769\u2013780. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-15937-4_64"},{"issue":"1","key":"3_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41438-020-00345-6","volume":"7","author":"L Zhang","year":"2020","unstructured":"Zhang, L., Xu, Z., Xu, D., Ma, J., Chen, Y., Fu, Z.: Growth monitoring of greenhouse lettuce based on a convolutional neural network. Hortic. Res. 7(1), 1\u201312 (2020). https:\/\/doi.org\/10.1038\/s41438-020-00345-6","journal-title":"Hortic. Res."},{"key":"3_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104484","volume":"106","author":"D Fuentes-Jimenez","year":"2021","unstructured":"Fuentes-Jimenez, D., et al.: Towards dense people detection with deep learning and depth images. Eng. Appl. Artif. Intell. 106, 104484 (2021). https:\/\/doi.org\/10.1016\/j.engappai.2021.104484","journal-title":"Eng. Appl. Artif. Intell."},{"key":"3_CR15","unstructured":"Hemming, S. (creator), de zwart, F. (creator), Elings, A. (creator), Bijlaard, M. (creator), van marrewijk, B. (creator), Petropoulou, A. (creator) (2021). 3rd autonomous greenhouse challenge: Online challenge lettuce images10.4121\/15023088"},{"key":"3_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.applthermaleng.2021.117335","volume":"197","author":"A Chakrabarty","year":"2021","unstructured":"Chakrabarty, A., Danielson, C., Bortoff, S.A., Laughman, C.R.: Accelerating self-optimization control of refrigerant cycles with Bayesian optimization and adaptive moment estimation. Appl. Therm. Eng. 197, 117335 (2021). https:\/\/doi.org\/10.1016\/j.applthermaleng.2021.117335","journal-title":"Appl. Therm. Eng."},{"key":"3_CR17","doi-asserted-by":"publisher","unstructured":"Fratello, M., Tagliaferri, R.: Decision trees and random forests. In: Encyclopedia of Bioinformatics and Computational Biology, pp. 374\u2013383. Academic Press, Oxford (2019). https:\/\/doi.org\/10.1016\/B978-0-12-809633-8.20337-3","DOI":"10.1016\/B978-0-12-809633-8.20337-3"},{"issue":"2","key":"3_CR18","doi-asserted-by":"publisher","first-page":"2021","DOI":"10.1007\/s11694-020-00793-7","volume":"15","author":"BH Cho","year":"2021","unstructured":"Cho, B.H., Koyama, K., Koseki, S.: Determination of \u2018Hass\u2019 avocado ripeness during storage by a smartphone camera using artificial neural network and support vector regression. J. Food Meas. Charact. 15(2), 2021\u20132030 (2021)","journal-title":"J. Food Meas. Charact."},{"key":"3_CR19","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"issue":"6","key":"3_CR20","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. Commun. ACM 60(6), 84\u201390 (2017)","journal-title":"Commun. ACM"},{"key":"3_CR21","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-44198-1_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,28]],"date-time":"2023-11-28T22:10:26Z","timestamp":1701209426000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-44198-1_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031441974","9783031441981"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-44198-1_3","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":"22 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Heraklion","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","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":"26 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"32","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2023\/","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":"easyacademia.org","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"947","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":"426","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":"22","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":"45% - 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":"2.4","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":"4","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"type of other papers accepted  : 9 Abstract","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}