{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T03:34:23Z","timestamp":1767065663324,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":15,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819743988"},{"type":"electronic","value":"9789819743995"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-981-97-4399-5_28","type":"book-chapter","created":{"date-parts":[[2024,7,6]],"date-time":"2024-07-06T16:01:52Z","timestamp":1720281712000},"page":"298-307","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Enhancing Fruit and\u00a0Vegetable Image Classification with\u00a0Attention Mechanisms in\u00a0Convolutional Neural Networks"],"prefix":"10.1007","author":[{"given":"Faidat Adekemi","family":"Akorede","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Man-Fai","family":"Leung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hangjun","family":"Che","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,7]]},"reference":[{"issue":"1","key":"28_CR1","first-page":"311","volume":"26","author":"J Wang","year":"2021","unstructured":"Wang, J., Wang, J., Han, Q.L.: Neurodynamics-based model predictive control of continuous-time under-actuated mechatronic systems. IEEE\/ASME Trans. Mechatron. 26(1), 311\u2013322 (2021)","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"Pu, X., Pan, B., Che, H.: Robust low-rank graph multi-view clustering via Cauchy norm minimization. Mathematics 11(13), 2940 (2023)","DOI":"10.3390\/math11132940"},{"issue":"7","key":"28_CR3","doi-asserted-by":"publisher","first-page":"2825","DOI":"10.1109\/TNNLS.2019.2957105","volume":"32","author":"MF Leung","year":"2021","unstructured":"Leung, M.F., Wang, J.: Minimax and biobjective portfolio selection based on collaborative neurodynamic optimization. IEEE Trans. Neural Netw. Learn. Syst. 32(7), 2825\u20132836 (2021)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"28_CR4","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Wan, S., Yeh, M.L., Ma, H.L., Chou, T.Y.: The robust study of deep learning recursive neural network for predicting of turbidity of water. Water 14(5), 761 (2022)","DOI":"10.3390\/w14050761"},{"key":"28_CR6","doi-asserted-by":"crossref","unstructured":"Lui, A.K.F., Chan, Y.H., Leung, M.F.: Modelling of destinations for data-driven pedestrian trajectory prediction in public buildings. In: 2021 IEEE International Conference on Big Data (Big Data), Orlando, pp. 1709\u20131717 (2021)","DOI":"10.1109\/BigData52589.2021.9671813"},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Bello, A., Ng, S.C., Leung, M.F.: A BERT framework to sentiment analysis of tweets. Sensors 23(1), 506 (2023)","DOI":"10.3390\/s23010506"},{"key":"28_CR8","doi-asserted-by":"crossref","unstructured":"Wang, P., Fan, E., Wang, P.: Comparative analysis of image classification algorithms based on traditional machine learning and deep learning. Pattern Recogn. Lett. 141, 61\u201367 (2021)","DOI":"10.1016\/j.patrec.2020.07.042"},{"key":"28_CR9","doi-asserted-by":"crossref","unstructured":"Chakravarthi, B., Ng, S.C., Ezilarasan, M.R., Leung, M.F.: EEG-based emotion recognition using hybrid CNN and LSTM classification. Front. Comput. Neurosci. 16, 1019776 (2022)","DOI":"10.3389\/fncom.2022.1019776"},{"key":"28_CR10","doi-asserted-by":"crossref","unstructured":"Gu, J., et al.: Recent advances in convolutional neural networks. Pattern Recogn. 77, 354\u2013377 (2018)","DOI":"10.1016\/j.patcog.2017.10.013"},{"issue":"3","key":"28_CR11","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1111\/exsy.12146","volume":"33","author":"Y Zhang","year":"2016","unstructured":"Zhang, Y., Phillips, P., Wang, S., Ji, G., Yang, J., Wu, J.: Fruit classification by biogeography-based optimization and feedforward neural network. Exp. Syst. 33(3), 239\u2013253 (2016)","journal-title":"Exp. Syst."},{"issue":"7","key":"28_CR12","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0219803","volume":"14","author":"L Liu","year":"2019","unstructured":"Liu, L., Li, Z., Lan, Y., Shi, Y., Cui, Y.: Design of a tomato classifier based on machine vision. PLoS ONE 14(7), e0219803 (2019)","journal-title":"PLoS ONE"},{"key":"28_CR13","doi-asserted-by":"crossref","unstructured":"Xiang, Q., Wang, X., Li, R., Zhang, G., Lai, J., Hu, Q.: Fruit image classification based on Mobilenetv2 with transfer learning technique. In: 3rd International Conference on Computer Science and Application Eengineering, pp. 1\u20137. Association for Computing Machinery, New York (2019)","DOI":"10.1145\/3331453.3361658"},{"issue":"2","key":"28_CR14","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0264586","volume":"17","author":"TB Shahi","year":"2022","unstructured":"Shahi, T.B., Sitaula, C., Neupane, A., Guo, W.: Fruit classification using attention-based MobileNetV2 for industrial applications. PLoS ONE 17(2), e0264586 (2022)","journal-title":"PLoS ONE"},{"key":"28_CR15","doi-asserted-by":"publisher","first-page":"2209","DOI":"10.1007\/s40747-020-00192-x","volume":"9","author":"G Xue","year":"2023","unstructured":"Xue, G., Liu, S., Ma, Y.: A hybrid deep learning-based fruit classification using attention model and convolution autoencoder. Complex Intell. Syst. 9, 2209\u20132219 (2023)","journal-title":"Complex Intell. Syst."}],"container-title":["Lecture Notes in Computer Science","Advances in Neural Networks \u2013 ISNN 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-4399-5_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,6]],"date-time":"2024-07-06T16:05:54Z","timestamp":1720281954000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-4399-5_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819743988","9789819743995"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-4399-5_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"7 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISNN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Weihai","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isnn2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conference.cs.cityu.edu.hk\/isnn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}