{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T22:39:13Z","timestamp":1743115153745,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030996185"},{"type":"electronic","value":"9783030996192"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-99619-2_3","type":"book-chapter","created":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T05:19:48Z","timestamp":1648617588000},"page":"23-32","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["XceptionUnetV1: A Lightweight DCNN for Biomedical Image Segmentation"],"prefix":"10.1007","author":[{"given":"Mohammad Faiz Iqbal","family":"Faiz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad Zafar","family":"Iqbal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,3,31]]},"reference":[{"key":"3_CR1","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: Convolutional Networks for Biomedical Image Segmentation, U-Net (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"5","key":"3_CR2","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1109\/LGRS.2018.2802944","volume":"15","author":"Z Zhang","year":"2018","unstructured":"Zhang, Z., Liu, Q., Wang, Y.: Road extraction by deep residual U-Net. IEEE Geosci. Remote Sens. Lett. 15(5), 749\u2013753 (2018)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"3_CR3","unstructured":"Wang, S., et al.: U-Net using stacked dilated convolutions for medical image segmentation (2020)"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Wang, J., Lv, P., Wang, H., Shi, C.: SAR-U-Net: squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography (2021)","DOI":"10.1016\/j.cmpb.2021.106268"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Chollet, F. Xception: deep learning with depthwise separable convolutions (2017)","DOI":"10.1109\/CVPR.2017.195"},{"key":"3_CR6","doi-asserted-by":"publisher","unstructured":"Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder-decoder with atrous separable convolution for semantic image segmentation. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11211, pp. 833\u2013851. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01234-2_49","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition (2015)","DOI":"10.1109\/CVPR.2016.90"},{"key":"3_CR8","unstructured":"Chen, L., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.: Semantic image segmentation with deep convolutional nets and fully connected CRFs (2016)"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Chen, L., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.: DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs (2017)","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"3_CR10","unstructured":"Jaeger, S., Candemir, S., Antani, S., W\u00e1ng, Y.X.J., Lu, P.X., Thoma, G.: Two public chest X-ray datasets for computer-aided screening of pulmonary diseases. Quant. Imaging Med. Surg. 4(6), 475 (2014)"},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Higgins, G., et al.: Final report of the meeting \u201cmodeling & simulation in medicine: towards an integrated framework\u201d: July 20-21, 2000, national library of medicine, National Institutes of Health, Bethesda, Maryland, USA. Comput. Aided Surg. 6(1), 32\u201339 (2001)","DOI":"10.1002\/igs.1008"},{"key":"3_CR12","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1109\/TMI.2013.2284099","volume":"33","author":"S Jaeger","year":"2014","unstructured":"Jaeger, S., et al.: Automatic tuberculosis screening using chest radiographs. IEEE Trans. Med. Imaging 33, 233\u2013245 (2014)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"3_CR13","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/TMI.2013.2290491","volume":"33","author":"S Candemir","year":"2014","unstructured":"Candemir, S., et al.: Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration. IEEE Trans. Med. Imaging 33, 577\u2013590 (2014)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"3_CR14","unstructured":"Kingma, D., Ba, J.: A Method for Stochastic Optimization. Adam (2017)"},{"key":"3_CR15","unstructured":"Chollet, F., et al.: Keras (2015). https:\/\/keras.io"}],"container-title":["Lecture Notes in Networks and Systems","Advanced Information Networking and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-99619-2_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T06:06:25Z","timestamp":1648620385000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-99619-2_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030996185","9783030996192"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-99619-2_3","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"31 March 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AINA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Information Networking and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 April 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 April 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aina2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/voyager.ce.fit.ac.jp\/conf\/aina\/2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}