{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T21:43:21Z","timestamp":1726177401464},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031149023"},{"type":"electronic","value":"9783031149030"}],"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"},{"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.springernature.com\/gp\/researchers\/text-and-data-mining"},{"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.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-14903-0_2","type":"book-chapter","created":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T19:03:00Z","timestamp":1666119780000},"page":"11-19","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DNM-SNN: Spiking Neural Network Based on Dual Network Model"],"prefix":"10.1007","author":[{"given":"Zhen","family":"Cao","sequence":"first","affiliation":[]},{"given":"Hongwei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Qian","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Chuanfeng","family":"Ma","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,19]]},"reference":[{"issue":"6088","key":"2_CR1","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1038\/323533a0","volume":"323","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. Nature 323(6088), 533\u2013536 (1986)","journal-title":"Nature"},{"key":"2_CR2","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, vol. 25 (2012)"},{"key":"2_CR3","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.neunet.2017.12.005","volume":"99","author":"SR Kheradpisheh","year":"2018","unstructured":"Kheradpisheh, S.R., Ganjtabesh, M., Thorpe, S.J., et al.: STDP-based spiking deep convolutional neural networks for object recognition. Neural Netw. 99, 56\u201367 (2018)","journal-title":"Neural Netw."},{"key":"2_CR4","doi-asserted-by":"publisher","first-page":"682","DOI":"10.3389\/fnins.2017.00682","volume":"11","author":"B Rueckauer","year":"2017","unstructured":"Rueckauer, B., Lungu, I.A., Hu, Y., et al.: Conversion of continuous-valued deep networks to efficient event-driven networks for image classification. Front. Neurosci. 11, 682 (2017)","journal-title":"Front. Neurosci."},{"issue":"1","key":"2_CR5","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1007\/s11263-014-0788-3","volume":"113","author":"Y Cao","year":"2015","unstructured":"Cao, Y., Chen, Y., Khosla, D.: Spiking deep convolutional neural networks for energy-efficient object recognition. Int. J. Comput. Vis. 113(1), 54\u201366 (2015)","journal-title":"Int. J. Comput. Vis."},{"key":"2_CR6","doi-asserted-by":"publisher","first-page":"95","DOI":"10.3389\/fnins.2019.00095","volume":"13","author":"A Sengupta","year":"2019","unstructured":"Sengupta, A., Ye, Y., Wang, R., et al.: Going deeper in spiking neural networks: VGG and residual architectures. Front. Neurosci. 13, 95 (2019)","journal-title":"Front. Neurosci."},{"issue":"3","key":"2_CR7","first-page":"577","volume":"43","author":"X Lin","year":"2015","unstructured":"Lin, X., Wang, X., Zhang, N., et al.: Supervised learning algorithms for spiking neural networks: a review. Acta Electonica Sinica 43(3), 577 (2015)","journal-title":"Acta Electonica Sinica"},{"key":"2_CR8","doi-asserted-by":"crossref","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 Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"2_CR9","unstructured":"Hu, Y., Tang, H., Pan, G.: Spiking deep residual networks. IEEE Trans. Neural Netw. Learn. Syst. (2018)"},{"key":"2_CR10","doi-asserted-by":"publisher","first-page":"987","DOI":"10.3389\/fnins.2018.00987","volume":"12","author":"D Zambrano","year":"2019","unstructured":"Zambrano, D., Nusselder, R., Scholte, H.S., et al.: Sparse computation in adaptive spiking neural networks. Front. Neurosci. 12, 987 (2019)","journal-title":"Front. Neurosci."},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Kim, S., Park, S., Na, B., et al.: Spiking-yolo: spiking neural network for energy-efficient object detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 07, pp. 11270\u201311277 (2020)","DOI":"10.1609\/aaai.v34i07.6787"},{"key":"2_CR12","first-page":"620","volume":"9","author":"L Lapique","year":"1907","unstructured":"Lapique, L.: Recherches quantitatives sur l\u2019excitation electrique des nerfs traitee comme une polarization. J. Physiol. Pathol. 9, 620\u2013635 (1907)","journal-title":"J. Physiol. Pathol."},{"key":"2_CR13","unstructured":"Dayan, P., Abbott, L.F.: Computational and Mathematical Modeling of Neural Systems. Theoretical Neuroscience. MIT Press (2001)"},{"key":"2_CR14","doi-asserted-by":"crossref","unstructured":"Han, B., Srinivasan, G., Roy, K.: RMP-SNN: residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13558\u201313567 (2020)","DOI":"10.1109\/CVPR42600.2020.01357"}],"container-title":["IFIP Advances in Information and Communication Technology","Intelligence Science IV"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-14903-0_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T02:03:09Z","timestamp":1672365789000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-14903-0_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031149023","9783031149030"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-14903-0_2","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"19 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligence Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xi'an","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":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icis2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.intsci.ac.cn\/icis2022\/home\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","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":"85","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":"44","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":"5","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":"52% - 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":"5","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)"}}]}}