{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T19:58:11Z","timestamp":1742932691429,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819601240"},{"type":"electronic","value":"9789819601257"}],"license":[{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-0125-7_12","type":"book-chapter","created":{"date-parts":[[2024,11,17]],"date-time":"2024-11-17T03:07:20Z","timestamp":1731812840000},"page":"139-151","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["TEBN: Texture-Enhanced Branching Network for\u00a0Fine-Grained Tea Classification"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-3457-4254","authenticated-orcid":false,"given":"Qijun","family":"Li","sequence":"first","affiliation":[]},{"given":"Xiaoqin","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Jinsong","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xianping","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Guogiang","family":"Xiao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,12]]},"reference":[{"key":"12_CR1","unstructured":"Chou, P.Y., Kao, Y.Y., Lin, C.H.: Fine-grained visual classification with high-temperature refinement and background suppression. arXiv preprint arXiv:2303.06442 (2023)"},{"key":"12_CR2","unstructured":"Chou, P.Y., Lin, C.H., Kao, W.C.: A novel plug-in module for fine-grained visual classification. arXiv preprint arXiv:2202.03822 (2022)"},{"key":"12_CR3","doi-asserted-by":"crossref","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Machine Learn. 20, 273\u2013297 (1995)","DOI":"10.1007\/BF00994018"},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"Dong, X., et al.: Cswin transformer: a general vision transformer backbone with cross-shaped windows. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12124\u201312134 (2022)","DOI":"10.1109\/CVPR52688.2022.01181"},{"key":"12_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.bios.2023.115447","volume":"237","author":"Y Fan","year":"2023","unstructured":"Fan, Y., et al.: Umami taste evaluation based on a novel mouse taste receptor cell-based biosensor. Biosens. Bioelectron. 237, 115447 (2023)","journal-title":"Biosens. Bioelectron."},{"issue":"1","key":"12_CR6","first-page":"75","volume":"3","author":"M Hall-Beyer","year":"2000","unstructured":"Hall-Beyer, M.: Glcm texture: a tutorial. National Council on Geographic Information and Analysis Remote Sensing Core Curriculum 3(1), 75 (2000)","journal-title":"National Council on Geographic Information and Analysis Remote Sensing Core Curriculum"},{"key":"12_CR7","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","volume":"6","author":"RM Haralick","year":"1973","unstructured":"Haralick, R.M., Shanmugam, K., Dinstein, I.H.: Textural features for image classification. IEEE Trans. Syst. Man Cybern. 6, 610\u2013621 (1973)","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"12_CR8","doi-asserted-by":"crossref","unstructured":"He, J., et al.: Transfg: a transformer architecture for fine-grained recognition. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a036, pp. 852\u2013860 (2022)","DOI":"10.1609\/aaai.v36i1.19967"},{"key":"12_CR9","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"},{"key":"12_CR10","doi-asserted-by":"crossref","unstructured":"Kane, D.M., Diakonikolas, I., Xiao, H., Liu, S.: Online robust mean estimation. In: Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 3197\u20133235. SIAM (2024)","DOI":"10.1137\/1.9781611977912.115"},{"key":"12_CR11","unstructured":"layer, V.: Visual layer (2023). https:\/\/visual-layer.readme.io\/"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"issue":"1","key":"12_CR13","first-page":"86","volume":"2","author":"F Murtagh","year":"2012","unstructured":"Murtagh, F., Contreras, P.: Algorithms for hierarchical clustering: an overview. Wiley Interdiscip. Rev.: Data Mining Knowl. Disc. 2(1), 86\u201397 (2012)","journal-title":"Wiley Interdiscip. Rev.: Data Mining Knowl. Disc."},{"issue":"7","key":"12_CR14","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","volume":"24","author":"T Ojala","year":"2002","unstructured":"Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971\u2013987 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"12_CR15","unstructured":"for Standardization, I.O.: Tea-classification of tea types. International Organization for Standardization, ISO 20715:2023 edn. (2023). https:\/\/www.iso.org\/standard\/75419.html"},{"key":"12_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.crfs.2023.100442","volume":"6","author":"D Wang","year":"2023","unstructured":"Wang, D., et al.: Comparative study of the volatile fingerprints of roasted and unroasted oolong tea by sensory profiling and hs-spme-gc-ms. Current Res. Food Sci. 6, 100442 (2023)","journal-title":"Current Res. Food Sci."},{"issue":"1\u20134","key":"12_CR17","first-page":"325","volume":"151","author":"S Wang","year":"2017","unstructured":"Wang, S., Phillips, P., Liu, A., Du, S.: Tea category identification using computer vision and generalized eigenvalue proximal svm. Fund. Inform. 151(1\u20134), 325\u2013339 (2017)","journal-title":"Fund. Inform."},{"issue":"20","key":"12_CR18","doi-asserted-by":"publisher","first-page":"7764","DOI":"10.3390\/s22207764","volume":"22","author":"K Wei","year":"2022","unstructured":"Wei, K., et al.: Classification of tea leaves based on fluorescence imaging and convolutional neural networks. Sensors 22(20), 7764 (2022)","journal-title":"Sensors"},{"key":"12_CR19","doi-asserted-by":"crossref","unstructured":"Xu, Q., Wang, J., Jiang, B., Luo, B.: Fine-grained visual classification via internal ensemble learning transformer. IEEE Transactions on Multimedia (2023)","DOI":"10.1109\/TMM.2023.3244340"},{"key":"12_CR20","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1007\/978-3-319-32557-6_5","volume-title":"High Performance Computing and Applications: Third International Conference, HPCA 2015, Shanghai, China, July 26-30, 2015, Revised Selected Papers","author":"X Zhou","year":"2016","unstructured":"Zhou, X., Zhang, G., Dong, Z., Wang, S., Zhang, Y.: Tea category classification based on feed-forward neural network and two-dimensional wavelet entropy. In: Xie, J., Chen, Z., Douglas, C.C., Zhang, W., Chen, Y. (eds.) High Performance Computing and Applications: Third International Conference, HPCA 2015, Shanghai, China, July 26-30, 2015, Revised Selected Papers, pp. 48\u201354. Springer International Publishing, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-32557-6_5"},{"issue":"3","key":"12_CR21","doi-asserted-by":"publisher","first-page":"1630","DOI":"10.1002\/jsfa.13049","volume":"104","author":"Y Zhu","year":"2024","unstructured":"Zhu, Y., et al.: Classification of oolong tea varieties based on computer vision and convolutional neural networks. J. Sci. Food Agric. 104(3), 1630\u20131637 (2024)","journal-title":"J. Sci. Food Agric."}],"container-title":["Lecture Notes in Computer Science","PRICAI 2024: Trends in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-0125-7_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,17]],"date-time":"2024-11-17T04:28:55Z","timestamp":1731817735000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-0125-7_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,12]]},"ISBN":["9789819601240","9789819601257"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-0125-7_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,12]]},"assertion":[{"value":"12 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kyoto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","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":"19 November 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 November 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pricai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.pricai.org\/2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}