{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T21:32:07Z","timestamp":1743024727127,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030302771"},{"type":"electronic","value":"9783030302788"}],"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\/978-3-030-30278-8_33","type":"book-chapter","created":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T16:01:51Z","timestamp":1567526511000},"page":"315-324","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Residual MobileNets"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1005-4315","authenticated-orcid":false,"given":"Adam","family":"Brzeski","sequence":"first","affiliation":[]},{"given":"Kamil","family":"Grinholc","sequence":"additional","affiliation":[]},{"given":"Kamil","family":"Nowodworski","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8231-709X","authenticated-orcid":false,"given":"Adam","family":"Przybylek","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,9,1]]},"reference":[{"key":"33_CR1","doi-asserted-by":"publisher","first-page":"64270","DOI":"10.1109\/ACCESS.2018.2877890","volume":"6","author":"Simone Bianco","year":"2018","unstructured":"Bianco, S., Cadene, R., Celona, L., Napoletano, P.: Benchmark analysis of representative deep neural network architectures. IEEE Access 6 (2018). https:\/\/doi.org\/10.1109\/ACCESS.2018.2877890","journal-title":"IEEE Access"},{"key":"33_CR2","doi-asserted-by":"crossref","unstructured":"Brzeski, A., Grinholc, K., Nowodworski, K., Przybylek, A.: Evaluating performance and accuracy improvements for attention-OCR. In: 18th International Conference on Computer Information Systems and Industrial Management Applications (CISIM 2019), Belgrade, Serbia (2019)","DOI":"10.1007\/978-3-030-28957-7_1"},{"key":"33_CR3","unstructured":"Byra, M., et al.: Impact of ultrasound image reconstruction method on breast lesion classification with neural transfer learning (2018). arXiv:1804.02119"},{"key":"33_CR4","doi-asserted-by":"crossref","unstructured":"Cychnerski, J., Brzeski, A., Boguszewski, A., Marmolowski, M., Trojanowicz, M.: Clothes detection and classification using convolutional neural networks. In: 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Limassol, Cyprus (2017)","DOI":"10.1109\/ETFA.2017.8247638"},{"key":"33_CR5","doi-asserted-by":"crossref","unstructured":"Gholami, A., et al.: SqueezeNext: hardware-aware neural network design. In: ECV Workshop at CVPR 2018, Utah, USA (2018)","DOI":"10.1109\/CVPRW.2018.00215"},{"key":"33_CR6","doi-asserted-by":"crossref","unstructured":"Han, D., Kim, J., Kim, J.: Deep pyramidal residual networks. In: 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI (2017)","DOI":"10.1109\/CVPR.2017.668"},{"key":"33_CR7","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"33_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"630","DOI":"10.1007\/978-3-319-46493-0_38","volume-title":"Computer Vision \u2013 ECCV 2016","author":"K He","year":"2016","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Identity mappings in deep residual networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9908, pp. 630\u2013645. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46493-0_38"},{"key":"33_CR9","unstructured":"Howard, A.G., et al.: MobileNets: efficient convolutional neural networks for mobile vision applications (2017). arXiv:1704.04861"},{"key":"33_CR10","unstructured":"Iandola, F.N., Han, S., Moskewicz, M.W., Ashraf, K., Dally, W.J., Keutzer, K.: SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and $$<$$0.5\u00a0MB model size (2016). arXiv:1602.07360"},{"key":"33_CR11","doi-asserted-by":"crossref","unstructured":"Jaderberg, M., Vedaldi, A., Zisserman, A.: Speeding up convolutional neural networks with low rank expansions. In: 2014 British Machine Vision Conference, Nottingham, UK (2014)","DOI":"10.5244\/C.28.88"},{"key":"33_CR12","doi-asserted-by":"crossref","unstructured":"Janczyk, K., Czuszynski, K., Ruminski, J.: Digits recognition with quadrant photodiode and convolutional neural network. In: 11th International Conference on Human System Interaction (HSI 2018), Gdansk, Poland (2018)","DOI":"10.1109\/HSI.2018.8431246"},{"key":"33_CR13","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)"},{"key":"33_CR14","doi-asserted-by":"crossref","unstructured":"Mehta, S., Rastegari, M., Shapiro, L., Hajishirzi, H.: ESPNetv2: a light-weight, power efficient, and general purpose convolutional neural network (2018). arXiv:1811.11431","DOI":"10.1109\/CVPR.2019.00941"},{"key":"33_CR15","doi-asserted-by":"publisher","unstructured":"Podlodowski, L., Roziewski, S., Nurzynski, M.: An ensemble of deep convolutional neural networks for marking hair follicles on microscopic images. In: 2018 Federated Conference on Computer Science and Information Systems (FedCSIS 2018), Poznan, Poland (2018). https:\/\/doi.org\/10.15439\/2018F389","DOI":"10.15439\/2018F389"},{"key":"33_CR16","doi-asserted-by":"crossref","unstructured":"Przybylek, K., Shkroba, I.: Crowd counting \u00e1 la Bourdieu. In: Workshop on Modern Approaches in Data Engineering and Information System Design at ADBIS 2019, Bled, Slovenia (2019)","DOI":"10.1007\/978-3-030-30278-8_31"},{"key":"33_CR17","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"33_CR18","doi-asserted-by":"crossref","unstructured":"Sandler, S., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.: MobileNetV2: inverted residuals and linear bottlenecks (2018). arXiv:1801.04381","DOI":"10.1109\/CVPR.2018.00474"},{"key":"33_CR19","doi-asserted-by":"crossref","unstructured":"Siam, M., Gamal, M., AbdelRazek, M., Yogomain, S., Jagersand, M., Zhang, H.: A comparative study of real-time semantic segmentation for autonomous driving. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, Utah, USA (2018)","DOI":"10.1109\/CVPRW.2018.00101"},{"key":"33_CR20","doi-asserted-by":"crossref","unstructured":"Zhang, X., Zhou, X., Lin, M., Sun, J.: ShuffleNet: an extremely efficient convolutional neural network for mobile devices (2017). arXiv:1707.01083","DOI":"10.1109\/CVPR.2018.00716"},{"issue":"6","key":"33_CR21","doi-asserted-by":"crossref","first-page":"1452","DOI":"10.1109\/TPAMI.2017.2723009","volume":"40","author":"B Zhou","year":"2018","unstructured":"Zhou, B., Lapedriza, A., Khosla, A., Oliva, A., Torralba, A.: Places: a 10 million image database for scene recognition. IEEE Trans. Pattern Anal. Mach. Intell. 40(6), 1452\u20131464 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Communications in Computer and Information Science","New Trends in Databases and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-30278-8_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T14:46:47Z","timestamp":1709822807000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-30278-8_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030302771","9783030302788"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-30278-8_33","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":"1 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ADBIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Advances in Databases and Information Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bled","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Slovenia","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":"8 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"adbis2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/adbis2019.um.si\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"103","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":"27","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":"19","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":"26% - 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":"3.15","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":"3.61","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"19 short papers are published in CCIS 1064","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)"}}]}}