This work is licensed under the Creative Commons Attribution 4.0 International License.
Alonso-Fernandez F., Bigun J., A survey on periocular biometrics research, Pattern Recognition Letters, 82(2), 92–105, 2016.Alonso-FernandezF.BigunJ.A survey on periocular biometrics researchPattern Recognition Letters822921052016Search in Google Scholar
Proença H., Neves J.C., Deep-PRWIS: Periocular recognition without the Iris and Sclera using deep learning frameworks, IEEE Transactions on Information Forensics and Security, 13(4), 888–896, 2018.ProençaH.NevesJ.C.Deep-PRWIS: Periocular recognition without the Iris and Sclera using deep learning frameworksIEEE Transactions on Information Forensics and Security1348888962018Search in Google Scholar
Lyle J.R., Miller P.E., Pundlik S.J., Woodard D.L., Soft biometric classification using local appearance periocular region features, Pattern Recognition, 45(11), 3877–3885, 2012.LyleJ.R.MillerP.E.PundlikS.J.WoodardD.L.Soft biometric classification using local appearance periocular region featuresPattern Recognition4511387738852012Search in Google Scholar
Tapia J., Viedma I., Gender classification from multispectral periocular images, IEEE International Joint Conference on Biometrics, 01–04 October 2017, Denver, Colorado, USA, 805–812, 2017.TapiaJ.ViedmaI.Gender classification from multispectral periocular imagesIEEE International Joint Conference on Biometrics01–04 October 2017Denver, Colorado, USA8058122017Search in Google Scholar
Lagree S., Bowyer K.W., Predicting ethnicity and gender from Iris texture, IEEE International Conference on Technologies for Homeland Security, 15–17 November 2011, Waltham, Massachusetts, USA, 440–445, 2011.LagreeS.BowyerK.W.Predicting ethnicity and gender from Iris textureIEEE International Conference on Technologies for Homeland Security15–17 November 2011Waltham, Massachusetts, USA4404452011Search in Google Scholar
Costa-Abreu M.D., Fairhurst M., Erbilek M., Exploring gender prediction from Iris biometrics, IEEE International Conference of the Biometrics Special Interest Group (BIOSIG), 09–11 September 2015, Darmstadt, Germany, 1–11, 2015.Costa-AbreuM.D.FairhurstM.ErbilekM.Exploring gender prediction from Iris biometricsIEEE International Conference of the Biometrics Special Interest Group (BIOSIG)09–11 September 2015Darmstadt, Germany1112015Search in Google Scholar
Singh M., Nagpal S., Vatsa M., Singh R., Noore A., Majumdar A., Gender and ethnicity classification of Iris images using deep class-encoder, IEEE International Joint Conference on Biometrics, 01–04 October 2017, Denver, Colorado, USA, 666–673, 2017.SinghM.NagpalS.VatsaM.SinghR.NooreA.MajumdarA.Gender and ethnicity classification of Iris images using deep class-encoderIEEE International Joint Conference on Biometrics01–04 October 2017Denver, Colorado, USA6666732017Search in Google Scholar
Bobeldyk D., Ross A., Iris or periocular? Exploring sex prediction from near infrared ocular images, 15th International Conference of the Biometrics Special Interest Group (BIOSIG), 21–23 September 2016, Darmstadt, Germany, 1–7, 2016.BobeldykD.RossA.Iris or periocular? Exploring sex prediction from near infrared ocular images15th International Conference of the Biometrics Special Interest Group (BIOSIG)21–23 September 2016Darmstadt, Germany172016Search in Google Scholar
Tapia J., Aravena C.C., Gender classification from periocular NIR images using fusion of CNNs models, IEEE 4th International Conference on Identity Security and Behavior Analysis, 11–12 January 2018, Singapore, 1–6, 2018.TapiaJ.AravenaC.C.Gender classification from periocular NIR images using fusion of CNNs modelsIEEE 4th International Conference on Identity Security and Behavior Analysis11–12 January 2018Singapore162018Search in Google Scholar
Merkow J., Jou B., Savvides M., An exploration of gender identification using only the periocular region, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), 27–29 September 2010, Washington, DC, USA 1–5, 2010.MerkowJ.JouB.SavvidesM.An exploration of gender identification using only the periocular region2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS)27–29 September 2010Washington, DC, USA152010Search in Google Scholar
Sun Z., Bebis G., Yuan X., Louis S.J., Genetic feature subset selection for gender classification: a comparison study, Sixth IEEE Workshop on Applications of Computer Vision, 04–04 December 2002, Orlando, Florida, USA, 165–170, 2002.SunZ.BebisG.YuanX.LouisS.J.Genetic feature subset selection for gender classification: a comparison studySixth IEEE Workshop on Applications of Computer Vision04–04 December 2002Orlando, Florida, USA1651702002Search in Google Scholar
Nguyen K., Fookes C., Ross A., Sridharan S., Iris recognition with off-the-shelf CNN features: A deep learning perspective, IEEE Access, 6, 18848–18855, 2018.NguyenK.FookesC.RossA.SridharanS.Iris recognition with off-the-shelf CNN features: A deep learning perspectiveIEEE Access618848188552018Search in Google Scholar
Razavian A.S., Azizpour H., Sullivan J., Carlsson S., CNN features off-the-shelf: An astounding baseline for recognition, IEEE Conference on Computer Vision and Pattern Recognition Workshops, 23–28 June 2014, Columbus, Ohio, USA, 512–519, 2014.RazavianA.S.AzizpourH.SullivanJ.CarlssonS.CNN features off-the-shelf: An astounding baseline for recognitionIEEE Conference on Computer Vision and Pattern Recognition Workshops23–28 June 2014Columbus, Ohio, USA5125192014Search in Google Scholar
Yosinski J., Clune J., Bengio Y., Lipson H., How transferable are features in deep neural networks?, 27th International Conference on Neural Information Processing Systems, Montreal, Canada, 8–13 December 2014, 2, 3320–3328, 2014.YosinskiJ.CluneJ.BengioY.LipsonH.How transferable are features in deep neural networks?27th International Conference on Neural Information Processing SystemsMontreal, Canada8–13 December 20142332033282014Search in Google Scholar
Tan M., Le Q.V., EfficientNet: Rethinking model scaling for convolutional neural networks, arXiv:1905.11946, 2019.TanM.LeQ.V.EfficientNet: Rethinking model scaling for convolutional neural networksarXiv:1905.11946,2019Search in Google Scholar
Park U., Ross A., Jain A.K., Periocular biometrics in the visible spectrum: A feasibility study, IEEE 3rd International Conference on Biometrics: Theory Applications and Systems, 28–30 September 2009, Washington, DC, USA, 1–6, 2009.ParkU.RossA.JainA.K.Periocular biometrics in the visible spectrum: A feasibility studyIEEE 3rd International Conference on Biometrics: Theory Applications and Systems28–30 September 2009Washington, DC, USA162009Search in Google Scholar
Bakshi S., Sa P.K., Majhi B., A novel phase-intensive local pattern for periocular recognition under visible spectrum, Biocybernetics and Biomedical Engineering, 35(1), 30–44, 2015.BakshiS.SaP.K.MajhiB.A novel phase-intensive local pattern for periocular recognition under visible spectrumBiocybernetics and Biomedical Engineering35130442015Search in Google Scholar
Zhao Z., Kumar A., Accurate periocular recognition under less constrained environment using semantics-assisted convolutional neural network, IEEE Transactions on Information Forensics and Security, 12(5), 1017–1030, 2017.ZhaoZ.KumarA.Accurate periocular recognition under less constrained environment using semantics-assisted convolutional neural networkIEEE Transactions on Information Forensics and Security125101710302017Search in Google Scholar
Agarwal V., Complete architectural details of all efficientnet models, https://towardsdatascience.com/complete-architectural-details-of-all-efficientnet-models-5fd5b736142, Accessed: November 22, 2022.AgarwalV.Complete architectural details of all efficientnet modelshttps://towardsdatascience.com/complete-architectural-details-of-all-efficientnet-models-5fd5b736142, Accessed: November 22, 2022.Search in Google Scholar
Pavelbiz, Female and male eyes, https://www.kaggle.com/datasets/pavelbiz/eyes-rtte, Accessed: July 10, 2021.Pavelbiz, Female and male eyeshttps://www.kaggle.com/datasets/pavelbiz/eyes-rtte, Accessed: July 10, 2021.Search in Google Scholar
Female and male eyes, https://ruskino.ru/, Accessed: July 10, 2021.Female and male eyeshttps://ruskino.ru/, Accessed: July 10, 2021.Search in Google Scholar