{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T22:56:19Z","timestamp":1780527379372,"version":"3.54.1"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819990047","type":"print"},{"value":"9789819990054","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-981-99-9005-4_60","type":"book-chapter","created":{"date-parts":[[2024,3,30]],"date-time":"2024-03-30T16:02:03Z","timestamp":1711814523000},"page":"477-483","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["YOLOv7-Tiny and YOLOv8n Evaluation for Face Detection"],"prefix":"10.1007","author":[{"given":"Ibrahim","family":"Al Amoudi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dzati Athiar","family":"Ramli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,3,31]]},"reference":[{"key":"60_CR1","doi-asserted-by":"crossref","unstructured":"Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition. CVPR 2001, vol 1. IEEE","DOI":"10.1109\/CVPR.2001.990517"},{"key":"60_CR2","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1023\/B:VISI.0000013087.49260.fb","volume":"57","author":"P Viola","year":"2004","unstructured":"Viola P, Jones MJ (2004) Robust real-time face detection. Int J Comput Vis 57:137\u2013154","journal-title":"Int J Comput Vis"},{"key":"60_CR3","first-page":"291","volume":"6","author":"A Jadhav","year":"2021","unstructured":"Jadhav A, Lone S, Matey S, Madamwar T, Jakhete S (2021) Survey on face detection algorithms. Int J Innov Sci Res Technol 6:291\u2013297","journal-title":"Int J Innov Sci Res Technol"},{"issue":"10","key":"60_CR4","doi-asserted-by":"publisher","first-page":"1499","DOI":"10.1109\/LSP.2016.2603342","volume":"23","author":"K Zhang","year":"2016","unstructured":"Zhang K, Zhang Z, Li Z, Qiao Y (2016) Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Sig Process Lett 23(10):1499\u20131503","journal-title":"IEEE Sig Process Lett"},{"key":"60_CR5","doi-asserted-by":"crossref","unstructured":"Lin TY, Goyal P, Girshick R, He K, Doll\u00e1r P (2017) Focal loss for dense object detection. In: Proceedings of the IEEE international conference on computer vision, pp 2980\u20132988","DOI":"10.1109\/ICCV.2017.324"},{"key":"60_CR6","unstructured":"Howard AG, Zhu M, Chen B, Kalenichenko D, Wang W, Weyand T et al (2017) Mobilenets: efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861"},{"key":"60_CR7","doi-asserted-by":"crossref","unstructured":"Zhang X, Zhou X, Lin M, Sun J (2018) Shufflenet: an extremely efficient convolutional neural network for mobile devices. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 6848\u20136856","DOI":"10.1109\/CVPR.2018.00716"},{"key":"60_CR8","doi-asserted-by":"crossref","unstructured":"Wang CY, Bochkovskiy A, Liao HYM (2022) YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. arXiv preprint arXiv:2207.02696","DOI":"10.1109\/CVPR52729.2023.00721"},{"key":"60_CR9","doi-asserted-by":"crossref","unstructured":"Ye B, Shi Y, Li H, Li L, Tong S (2021) Face SSD: a real-time face detector based on SSD. In: Proceedings of the 2021 40th Chinese control conference (CCC). IEEE, pp 8445\u20138450","DOI":"10.23919\/CCC52363.2021.9550294"},{"key":"60_CR10","unstructured":"Bazarevsky V, Kartynnik Y, Vakunov A, Raveendran K, Grundmann M (2019) Blazeface: sub-millisecond neural face detection on mobile GPUs. arXiv preprint arXiv:1907.05047"},{"key":"60_CR11","doi-asserted-by":"crossref","unstructured":"Zhu X, Lou Y (2022) An efficient anchor-free face detector with attention mechanisms. Sci Program","DOI":"10.1155\/2022\/3856424"},{"key":"60_CR12","unstructured":"YOLOv8 Docs\u2019. https:\/\/docs.ultralytics.com\/#ultralytics-yolov8"},{"key":"60_CR13","unstructured":"Redmon J, Farhadi A (2018) Yolov3: an incremental improvement. arXiv preprint arXiv:1804.02767"},{"key":"60_CR14","unstructured":"Bochkovskiy A, Wang CY, Liao HYM (2020) Yolov4: optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934"},{"key":"60_CR15","unstructured":"GitHub: ultralytics\/yolov5: YOLOv5 in PyTorch > ONNX > CoreML > TFLite. https:\/\/github.com\/ultralytics\/yolov5"},{"key":"60_CR16","doi-asserted-by":"crossref","unstructured":"Wang CY, Bochkovskiy A, Liao HYM (2021) Scaled-yolov4: scaling cross stage partial network. In: Proceedings of the IEEE\/cvf conference on computer vision and pattern recognition, pp 13029\u201313038","DOI":"10.1109\/CVPR46437.2021.01283"},{"key":"60_CR17","doi-asserted-by":"crossref","unstructured":"Yang S, Luo P, Loy CC, Tang X (2016) Wider face: a face detection benchmark. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5525\u20135533","DOI":"10.1109\/CVPR.2016.596"}],"container-title":["Lecture Notes in Electrical Engineering","Proceedings of the 12th International Conference on Robotics, Vision, Signal Processing and Power Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-9005-4_60","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T09:41:16Z","timestamp":1731663676000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-9005-4_60"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819990047","9789819990054"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-9005-4_60","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"value":"1876-1100","type":"print"},{"value":"1876-1119","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"31 March 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"RoViSP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Robotics, Vision, Signal Processing and Power Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 April 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 April 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"rovisp2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}