[4]Minaee S, Boykov YY, Porikli F, et al. Image seg-mentation using deep learning: A survey[J]. IEEE Transac-tions on Pattern Analysis and Machine Intelligence, 2021.
[5]Harikrishnan J, Sudarsan A, Sadashiv A, et al.Vision-face recognition attendance monitoring system forsurveillance using deep learning technology and computervision[C]//2019 International Conference on Vision To-wards Emerging Trends in Communication and Networking(ViTECoN). IEEE, 2019: 1-5.
[6]Dickmanns E D, Zapp A. Autonomous high speed roadvehicle guidance by computer vision[J]. IFAC ProceedingsVolumes, 1987, 20(5): 221-226.
[7]Wang G, Zuluaga M A, Li W, et al. DeepIGeoS: a deepinteractive geodesic framework for medical imagesegmentation[J]. IEEE transactions on pattern analysisand machine intelligence, 2018, 41(7): 1559-1572.
[8]Qu Z, Mei J, Liu L, et al. Crack detection ofconcrete pavement with cross-entropy loss function andimproved VGG16 network model[J]. IEEE Access, 2020, 8:54564-54573.
[9]Klein S, Pluim J P W, Staring M, et al. Adaptivestochastic gradient descent optimisation for imageregistration[J]. International journal of computer vision,2009, 81(3): 227.
[10]Tovar E, Vasques F, Burns A. Supporting real-timedistributed computer-controlled systems with multi-hop P-NET networks[J]. Control Engineering Practice, 1999, 7(8): 1015-1025.
[11]Nobis F, Geisslinger M, Weber M, et al. A deeplearning-based radar and camera sensor fusion architec-ture for object detection[C]//2019 Sensor Data Fusion:Trends, Solutions, Applications (SDF). IEEE, 2019: 1-7.
[12]Viprey V F, Corrias M V, Kagedal B, et al.Standardisation of operating procedures for the detectionof minimal disease by QRT-PCR in children with neuroblastoma:quality assurance on behalf of SIOPEN-R-NET[J]. EuropeanJournal of Cancer, 2007, 43(2): 341-350.
