{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T08:09:31Z","timestamp":1783930171354,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819235032","type":"print"},{"value":"9789819235049","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3504-9_26","type":"book-chapter","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T07:35:40Z","timestamp":1783928140000},"page":"315-326","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["EAM-YOLO: Adaptive Feature Aggregation and Refined Regression for Robust Fall Detection"],"prefix":"10.1007","author":[{"given":"Yumeng","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihua","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoqing","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zenghui","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xu","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lisheng","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,14]]},"reference":[{"key":"26_CR1","doi-asserted-by":"publisher","first-page":"1708","DOI":"10.1016\/j.jamda.2023.06.002","volume":"24","author":"L Shao","year":"2023","unstructured":"Shao, L., Shi, Y., Xie, X.-Y., Wang, Z., Wang, Z.-A., Zhang, J.-E.: Incidence and risk factors of falls among older people in nursing homes: systematic review and meta-analysis. J. Am. Med. Dir. Assoc. 24, 1708\u20131717 (2023)","journal-title":"J. Am. Med. Dir. Assoc."},{"key":"26_CR2","doi-asserted-by":"publisher","first-page":"5212","DOI":"10.3390\/s23115212","volume":"23","author":"NT Newaz","year":"2023","unstructured":"Newaz, N.T., Hanada, E.: The methods of fall detection: a literature review. Sensors. 23, 5212 (2023)","journal-title":"Sensors"},{"key":"26_CR3","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1186\/s40537-021-00444-8","volume":"8","author":"L Alzubaidi","year":"2021","unstructured":"Alzubaidi, L., et al.: Review of deep learning: concepts, CNN architectures, challenges, applications, future directions. J. Big Data. 8, 53 (2021)","journal-title":"J. Big Data"},{"key":"26_CR4","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/JPROC.2023.3238524","volume":"111","author":"Z Zou","year":"2023","unstructured":"Zou, Z., Chen, K., Shi, Z., Guo, Y., Ye, J.: Object detection in 20 years: a survey. Proc. IEEE. 111, 257\u2013276 (2023)","journal-title":"Proc. IEEE"},{"key":"26_CR5","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. Adv. Neural Inf. Process. Syst. 28, 91\u201399 (2015)"},{"key":"26_CR6","volume-title":"ultralytics\/yolov5: v3.0","author":"G Jocher","year":"2020","unstructured":"Jocher, G., et al.: ultralytics\/yolov5: v3.0. Zenodo (2020)"},{"key":"26_CR7","first-page":"7464","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"C-Y Wang","year":"2023","unstructured":"Wang, C.-Y., Bochkovskiy, A., Liao, H.-Y.M.: YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7464\u20137475 (2023)"},{"key":"26_CR8","volume-title":"Ultralytics YoloV8","author":"G Jocher","year":"2024","unstructured":"Jocher, G., Chaurasia, A., Qiu, J.: Ultralytics YoloV8. 2023, (2024)"},{"key":"26_CR9","volume-title":"Ultralytics Yolo11","author":"G Jocher","year":"2024","unstructured":"Jocher, G., Qiu, J., Chaurasia, A.: Ultralytics Yolo11. gitHub repository. (2024)"},{"key":"26_CR10","unstructured":"Tian, Y., Ye, Q., Doermann, D.: Yolov12: attention-centric real-time object detectors. arXiv preprint arXiv:2502.12524. (2025)"},{"key":"26_CR11","first-page":"21","volume-title":"European Conference on Computer Vision","author":"W Liu","year":"2016","unstructured":"Liu, W., et al.: Ssd: single shot multibox detector. In: European Conference on Computer Vision, pp. 21\u201337. Springer (2016)"},{"key":"26_CR12","first-page":"2980","volume-title":"Proceedings of the IEEE International Conference on Computer Vision","author":"T-Y Lin","year":"2017","unstructured":"Lin, T.-Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)"},{"key":"26_CR13","volume":"2022","author":"Q Wang","year":"2022","unstructured":"Wang, Q.: Application of human posture recognition based on the convolutional neural network in physical training guidance. Comput. Intell. Neurosci. 2022, 5277157 (2022)","journal-title":"Comput. Intell. Neurosci."},{"key":"26_CR14","doi-asserted-by":"publisher","first-page":"16802","DOI":"10.1038\/s41598-022-20983-1","volume":"12","author":"X Jiang","year":"2022","unstructured":"Jiang, X., Hu, H., Qin, Y., Hu, Y., Ding, R.: A real-time rural domestic garbage detection algorithm with an improved YOLOv5s network model. Sci. Rep. 12, 16802 (2022)","journal-title":"Sci. Rep."},{"key":"26_CR15","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1007\/s10462-025-11253-3","volume":"58","author":"R Sapkota","year":"2025","unstructured":"Sapkota, R., et al.: YOLO advances to its genesis: a decadal and comprehensive review of the You Only Look Once (YOLO) series. Artif. Intell. Rev. 58, 274 (2025)","journal-title":"Artif. Intell. Rev."},{"key":"26_CR16","first-page":"16965","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Y Zhao","year":"2024","unstructured":"Zhao, Y., et al.: Detrs beat yolos on real-time object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 16965\u201316974 (2024)"},{"key":"26_CR17","doi-asserted-by":"publisher","first-page":"15219","DOI":"10.1109\/JSEN.2024.3375603","volume":"24","author":"S Campanella","year":"2024","unstructured":"Campanella, S., Alnasef, A., Falaschetti, L., Belli, A., Pierleoni, P., Palma, L.: A novel embedded deep learning wearable sensor for fall detection. IEEE Sensors J. 24, 15219\u201315229 (2024). https:\/\/doi.org\/10.1109\/JSEN.2024.3375603","journal-title":"IEEE Sensors J."},{"key":"26_CR18","doi-asserted-by":"publisher","first-page":"648","DOI":"10.3390\/s24020648","volume":"24","author":"T Liang","year":"2024","unstructured":"Liang, T., Liu, R., Yang, L., Lin, Y., Shi, C.-J.R., Xu, H.: Fall detection system based on point cloud enhancement model for 24 GHz FMCW radar. Sensors. 24, 648 (2024)","journal-title":"Sensors"},{"key":"26_CR19","first-page":"30178","volume-title":"Proceedings of the Computer Vision and Pattern Recognition Conference","author":"L Chen","year":"2025","unstructured":"Chen, L., Gu, L., Li, L., Yan, C., Fu, Y.: Frequency dynamic convolution for dense image prediction. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 30178\u201330188 (2025)"},{"key":"26_CR20","doi-asserted-by":"publisher","first-page":"2026","DOI":"10.1038\/s41598-025-86593-9","volume":"15","author":"X Huang","year":"2025","unstructured":"Huang, X., et al.: SDES-YOLO: a high-precision and lightweight model for fall detection in complex environments. Sci. Rep. 15, 2026 (2025)","journal-title":"Sci. Rep."},{"key":"26_CR21","doi-asserted-by":"publisher","first-page":"5069","DOI":"10.1038\/s41598-025-89214-7","volume":"15","author":"H Wang","year":"2025","unstructured":"Wang, H., Xu, S., Chen, Y., Su, C.: LFD-YOLO: a lightweight fall detection network with enhanced feature extraction and fusion. Sci. Rep. 15, 5069 (2025)","journal-title":"Sci. Rep."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3504-9_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T07:35:42Z","timestamp":1783928142000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3504-9_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,14]]},"ISBN":["9789819235032","9789819235049"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3504-9_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,14]]},"assertion":[{"value":"14 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}