ABSTRACT
Contactless fingerprints have continued to grow interoperability as a faster and more convenient replacement for contact fingerprints, and with covid-19 now starting to be a past event the need for hygienic alternatives has only grown after the sudden focus during the pandemic. Though, past works have shown issues with the interoperability of contactless prints from both kiosk devices and phone fingerprint collection apps. The focus of the paper is the evaluation of match performance between contact and contactless fingerprints, and the evaluation of match score bias based on skin demographics. AUC results indicate contactless match performance is as good as contact fingerprints, while phone contactless fingerprints fall short. Additionally, bias found for melanin showed specific ranges effected in both low melanin values and high melanin values.
ABSTRACT
In recent years, periocular recognition has been developed as a valuable biometric identification approach, especially in wild environments (for example, masked faces due to COVID-19 pandemic) where facial recognition may not be applicable. This paper presents a new deep periocular recognition framework called attribute-based deep periocular recognition (ADPR), which predicts soft biometrics and incorporates the prediction into a periocular recognition algorithm to determine identity from periocular images with high accuracy. We propose an end-to-end framework, which uses several shared convolutional neural network (CNN) layers (a common network) whose output feeds two separate dedicated branches (modality dedicated layers);the first branch classifies periocular images while the second branch predicts soft biometrics. Next, the features from these two branches are fused together for a final periocular recognition. The proposed method is different from existing methods as it not only uses a shared CNN feature space to train these two tasks jointly, but it also fuses predicted soft biometric features with the periocular features in the training step to improve the overall periocular recognition performance. Our proposed model is extensively evaluated using four different publicly available datasets. Experimental results indicate that our soft biometric based periocular recognition approach outperforms other state-of-the-art methods for periocular recognition in wild environments.
ABSTRACT
BACKGROUND: Recently, outbreak of novel coronavirus (CoV) (severe acute respiratory syndrome-CoV-2 [SARS-CoV-2]) has been emerged as a serious public health concern. On February 11, 2020, the WHO announced an official name for this disease, CoV disease-(COVID)-19. The virus can cause systemic complications such as lung involvement, skin, and oral complications. AIM: The aim of this study was to review of the oral manifestations of COVID-19. METHODS: In this narrative review study, we searched all articles between 2010 and 2020 in PubMed, Scopus, Science Direct related to COVID-19, and its oral manifestations, using the following terms: “Coronavirus,” “COVID-19,” and “SARS-CoV-2” in combination with “Stomatognathic diseases,” “Oral manifestation,” and “Mouth diseases.” RESULTS: The most common oral manifestations in people with COVID-19 that we get after searching are: salivary gland disease, xerostomia, taste and smell alterations, and oral mucosal lesions. CONCLUSIONS: Since almost all of the oral findings appear at the asymptomatic phase of disease, identification of these symptoms can help to timely diagnosis of the main disease.
ABSTRACT
Aim: One of the main factors that play a pivotal role in the transmission of COVID-19 from human to human is saliva;according to the subject's importance, the present study aimed to evaluate the potential of transmission via the saliva of coronavirus disease. Methods: PubMed, ISI, Embase, Scopus, Medicine have been used until September 2020 to search for articles. Therefore, EndNote X9 used to manage electronic resources. A 95% confidence interval (CI) effect size, fixed effect model, Inverse-variance methods have been calculated. The positive rate of SARS-CoV2 assessed with meta analysis. To deal with potential heterogeneity, random effects were used, and I2 showed heterogeneity. I2 values above 50% signified moderate-to-high heterogeneity. The Meta-analysis has been evaluated with Stata/MP v.16 (the fastest version of Stata) statistical software. Results: According to the study's purpose, in the initial search with keywords, 19 articles were found, the full text of 3 studies was reviewed, and finally, three studies were selected. The positive rate of SARS-CoV2 was 86% (86%;95% CI 67 %-100%). Conclusion: saliva can be a non-invasive specimen type for diagnosis of COVID-19. Dentists should be aware that saliva plays a major role in the transmission of COVID-19 from human to human, and failure to follow prevention protocols can contaminate them. © 2021. All Rights Reserved.