{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T11:23:11Z","timestamp":1751714591951},"publisher-location":"Singapore","reference-count":16,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811399169"},{"type":"electronic","value":"9789811399176"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-981-13-9917-6_45","type":"book-chapter","created":{"date-parts":[[2019,7,19]],"date-time":"2019-07-19T09:05:04Z","timestamp":1563527104000},"page":"472-481","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Plant Identification Based on Multi-branch Convolutional Neural Network with Attention"],"prefix":"10.1007","author":[{"given":"Pengxi","family":"Li","sequence":"first","affiliation":[]},{"given":"Xiaoqing","family":"Gong","sequence":"additional","affiliation":[]},{"given":"Xu","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Lianqi","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Xiaoting","family":"Xue","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Pengfei","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Daguang","family":"Gan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,7,20]]},"reference":[{"issue":"6","key":"45_CR1","first-page":"834","volume":"42","author":"W Guan","year":"2016","unstructured":"Guan, W., Xue, X., An, Z.: Application progress and prospect of deep learning in video target tracking. Acta Automatica Sinica 42(6), 834\u2013847 (2016)","journal-title":"Acta Automatica Sinica"},{"key":"45_CR2","unstructured":"Qi, H., Shou, W., Jin, S.: Computer-aided plant identification model based on leaf features (2003)"},{"issue":"3","key":"45_CR3","first-page":"394","volume":"30","author":"W Chen","year":"2013","unstructured":"Chen, W., Zhou, P.: Research on leaf shape and texture feature extraction of plants. J. Zhejiang Sci-Tech Univ. 30(3), 394\u2013398 (2013)","journal-title":"J. Zhejiang Sci-Tech Univ."},{"issue":"5","key":"45_CR4","first-page":"12","volume":"35","author":"L Wei","year":"2013","unstructured":"Wei, L., He, D.J., Qiao, Y.L.: Plant leaves classification based on image processing and SVM. J. Agric. Mech. Res. 35(5), 12\u201315 (2013)","journal-title":"J. Agric. Mech. Res."},{"key":"45_CR5","first-page":"6","volume":"2017","author":"Y Sun","year":"2017","unstructured":"Sun, Y., et al.: Deep learning for plant identification in natural environment. Comput. Intell. Neurosci. 2017, 6 (2017). Article no. 7361042","journal-title":"Comput. Intell. Neurosci."},{"key":"45_CR6","doi-asserted-by":"crossref","unstructured":"Wu, S.G., Bao, F.S., Xu, E.Y., et al.: A leaf recognition algorithm for plant classification using probabilistic neural network. In: 2007 IEEE International Symposium on Signal Processing and Information Technology, pp. 11\u201316. IEEE (2007)","DOI":"10.1109\/ISSPIT.2007.4458016"},{"issue":"2","key":"45_CR7","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1109\/LGRS.2015.2501383","volume":"13","author":"S Chaib","year":"2016","unstructured":"Chaib, S., Gu, Y.F., Yao, H.X.: An informative feature selection method based on sparse PCA for VHR scene classification. IEEE Geosci. Remote Sens. Lett. 13(2), 147\u2013151 (2016)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"11","key":"45_CR8","first-page":"136","volume":"27","author":"S Fan","year":"2018","unstructured":"Fan, S., Wang, X., Qi, Z.: Fast recognition of space plants image based on fully convolutional networks. J. Comput. Syst. 27(11), 136\u2013141 (2018)","journal-title":"J. Comput. Syst."},{"issue":"9","key":"45_CR9","first-page":"108","volume":"38","author":"S Zhang","year":"2016","unstructured":"Zhang, S., Huai, Y.J.: Leaf image recognition based on neural network deep learning. J. Beijing Forestry Univ. 38(9), 108\u2013115 (2016)","journal-title":"J. Beijing Forestry Univ."},{"key":"45_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1007\/978-3-319-10590-1_53","volume-title":"Computer Vision \u2013 ECCV 2014","author":"MD Zeiler","year":"2014","unstructured":"Zeiler, M.D., Fergus, R.: Visualizing and understanding convolutional networks. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8689, pp. 818\u2013833. Springer, Cham (2014). \n                  https:\/\/doi.org\/10.1007\/978-3-319-10590-1_53"},{"key":"45_CR11","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint \n                  arXiv:1409.1556\n                  \n                 (2014)"},{"key":"45_CR12","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., Jia, Y., et al.: Going deeper with convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20139 (2015)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"45_CR13","unstructured":"He, K., Zhang, X., Ren, S., et al.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern"},{"key":"45_CR14","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., et al.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"45_CR15","unstructured":"Liao, J., Cai, Y., Wang, Y., et al.: Plant disease identification technology based on convolutional neural network. Mod. Comput. (Prof. Ed.) (2018 19), 43\u201348, 53 (2018)"},{"key":"45_CR16","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, pp. 1097\u20131105 (2012)"}],"container-title":["Communications in Computer and Information Science","Image and Graphics Technologies and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-13-9917-6_45","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,19]],"date-time":"2019-07-19T09:23:20Z","timestamp":1563528200000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-13-9917-6_45"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9789811399169","9789811399176"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-981-13-9917-6_45","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"20 July 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IGTA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Image and Graphics Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Beijing","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":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"igta0","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.bsig.org.cn\/list\/IGTA","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"152","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":"66","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":"43% - 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":"8","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)"}}]}}