{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:36:00Z","timestamp":1742913360878,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031213328"},{"type":"electronic","value":"9783031213335"}],"license":[{"start":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T00:00:00Z","timestamp":1668988800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T00:00:00Z","timestamp":1668988800000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-21333-5_12","type":"book-chapter","created":{"date-parts":[[2022,11,20]],"date-time":"2022-11-20T19:02:43Z","timestamp":1668970963000},"page":"119-124","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Fine-Tuning AlexNet for Bed Occupancy Detection in Low-Resolution Thermal Sensor Images"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6419-8819","authenticated-orcid":false,"given":"Rebecca","family":"Hand","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2368-7354","authenticated-orcid":false,"given":"Ian","family":"Cleland","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0882-7902","authenticated-orcid":false,"given":"Chris","family":"Nugent","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,21]]},"reference":[{"key":"12_CR1","doi-asserted-by":"crossref","unstructured":"William, J., Cook, D.: Forecasting Behavior in Smart Homes Based on Sleep and Wake Patterns. Technology and Health Care, vol. 25 (2017)","DOI":"10.3233\/THC-161255"},{"key":"12_CR2","doi-asserted-by":"crossref","unstructured":"Popescu, M.: Early Illness Detection in Elderly using Sensor Networks: A Review of the TigerPlace Experience. EHB (2015)","DOI":"10.1109\/EHB.2015.7391386"},{"key":"12_CR3","doi-asserted-by":"crossref","unstructured":"Liao, W., Yang, C: Video-Based Activity and Movement Pattern Analysis in Overnight Sleep Studies. ICPR (2009)","DOI":"10.1109\/ICPR.2008.4761635"},{"key":"12_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1007\/978-3-319-24195-1_3","volume-title":"Human Behavior Understanding","author":"M Eldib","year":"2015","unstructured":"Eldib, M., Deboeverie, F., Philips, W., Aghajan, H.: Sleep Analysis for Elderly Care Using a Low-Resolution Visual Sensor Network. In: Salah, A.A., Kr\u00f6se, B.J.A., Cook, D.J. (eds.) HBU 2015. LNCS, vol. 9277, pp. 26\u201338. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24195-1_3"},{"key":"12_CR5","unstructured":"Hand, R., et al.: The Use of Thermal Sensing Technology to Detect Bed Occupancy: A Feasibility Study. LNICST. vol. 431 (2022)"},{"key":"12_CR6","doi-asserted-by":"crossref","unstructured":"Zheng, Y.: Evaluation and Implementation of Convolutional Neural Networks in Image Recognition. Journal of Physics: Conf. Series 1087 (2018)","DOI":"10.1088\/1742-6596\/1087\/6\/062018"},{"key":"12_CR7","doi-asserted-by":"crossref","unstructured":"Sultana, F., et al.: Advancements in Image Classification using Convolutional Neural Network. RCICN (2018)","DOI":"10.1109\/ICRCICN.2018.8718718"},{"key":"12_CR8","doi-asserted-by":"crossref","unstructured":"Jmour, N., et al.: Convolutional Neural Networks for Image Classification. ASET (2018)","DOI":"10.1109\/ASET.2018.8379889"},{"key":"12_CR9","doi-asserted-by":"crossref","unstructured":"Kumar, A., et al.: An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification. IEEE J. Biomed. Health Inform (2017)","DOI":"10.1109\/JBHI.2016.2635663"},{"key":"12_CR10","doi-asserted-by":"crossref","unstructured":"Tajbakhsh, N., et al.: Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?. T-MI (2016)","DOI":"10.1109\/TMI.2016.2535302"},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"Wang, S.H., et al.: Alcoholism identification based on an alexnet transfer learning model. Frontiers in Psychiatry 10 (2019)","DOI":"10.3389\/fpsyt.2019.00205"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Cetinic, D., et al.: Fine-tuning convolutional neural networks for fine art classification. Expert Systems With Applications 114 (2018)","DOI":"10.1016\/j.eswa.2018.07.026"},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Medina-Quero, J., et al.: Detection of Falls from Non-Invasive Thermal Vision Sensors Using Convolutional Neural Networks. UCAmI (2018)","DOI":"10.3390\/proceedings2191236"},{"key":"12_CR14","doi-asserted-by":"crossref","unstructured":"Rafferty, J., et al.: Thermal Vision Based Fall Detection via Logical and Data driven Processes. BCD (2019)","DOI":"10.1109\/BCD.2019.8884820"},{"key":"12_CR15","doi-asserted-by":"crossref","unstructured":"Burns, M., et al.: Using Convolutional Neural Networks with Multiple Thermal Sensors for Unobtrusive Pose Recognition. Sensors (2020)","DOI":"10.3390\/s20236932"},{"key":"12_CR16","doi-asserted-by":"crossref","unstructured":"Acquaah, Y., et al.: Occupancy Detection for Smart HVAC Efficiency in Building Energy: A Deep Learning Neural Network Framework using Thermal Imagery. AIPR (2020)","DOI":"10.1109\/AIPR50011.2020.9425091"},{"key":"12_CR17","unstructured":"Leo, H., et al.: Fine Tuning CNN Pre-trained Model Based on Thermal Imaging for Obesity Early Detection. JRE (2020)"},{"key":"12_CR18","doi-asserted-by":"crossref","unstructured":"Roslidar, R., et al.: A Study of Fine-Tuning CNN Models Based on Thermal Imaging for Breast Cancer Classification. CyberneticsCom (2019)","DOI":"10.1109\/CYBERNETICSCOM.2019.8875661"},{"key":"12_CR19","doi-asserted-by":"crossref","unstructured":"Hosny, K., et al.: Classification of Skin Lesions into Seven Classes Using Transfer Learning with AlexNet. JDI (2020)","DOI":"10.1007\/s10278-020-00371-9"},{"key":"12_CR20","doi-asserted-by":"crossref","unstructured":"Lu, S., et al.: Pathological Brain Detection Based on AlexNet and Transfer Learning. Journal of Computational Science 30 (2019)","DOI":"10.1016\/j.jocs.2018.11.008"}],"container-title":["Lecture Notes in Networks and Systems","Proceedings of the International Conference on Ubiquitous Computing &amp; Ambient Intelligence (UCAmI 2022)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-21333-5_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,20]],"date-time":"2022-11-20T19:04:01Z","timestamp":1668971041000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-21333-5_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,21]]},"ISBN":["9783031213328","9783031213335"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-21333-5_12","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2022,11,21]]},"assertion":[{"value":"21 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"UCAmI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Ubiquitous Computing and Ambient Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"C\u00f3rdoba","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","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":"29 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ucami2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/mamilab.eu\/ucami2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}