Relevant bibliographies by topics / Age estimation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Age estimation'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Age estimation"

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KRYVENCHUK, Yurii, and Roman YAKYMIV. "CREATION OF AGE ESTIMATION SYSTEM." Herald of Khmelnytskyi National University. Technical sciences 309, no. 3 (May 26, 2022): 66–69. http://dx.doi.org/10.31891/2307-5732-2022-309-3-66-69.

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We are surrounded by different transmitting and processing information devices on a daily basis. Analysis of certain selected characteristics of each person allows humanity to achieve previously unthinkable technological development. In particular, the human face. We can predict a person’s age, determine his mood or identify someone in the crowd using modern algorithms. As a “window to the soul”, the human face provides important information related to its individual traits. With the help of this information, a person can determine such characteristics as ethnic origin, gender, age, and emotions, on the basis of which he is able to take appropriate action, which plays a significant role in non-verbal communication between people. Age estimation is useful in applications where you do not need to specifically identify a person, but we want to know (approximate) their age. With the help of the age approximation system, it is possible to ensure partial digitalization of security control and monitoring systems. With the help of a monitoring camera, the age estiomation system can identify minors and prevent them from entering places where they are not allowed; not to allow minors to buy tobacco products or alcohol from vending machines; to warn the elderly person of possible danger. Age assessment software can also be used in healthcare systems. The authors personally are interested in approximating human age based on images to personalize human-machine interaction. The paper has the description and the results of the creation of an age estimation system, the basis of which is a convolutional neural network. The user can connect with the system through a simple interface which allows you to upload the image for analysis or turn on the camera to get age estimates in real-time. The practical value of this work is the developed high-quality system which is ready for use and implementation in the relevant fields.
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Liversidge, Helen M., Jo Buckberry, and Nicholas Marquez-Grant. "Age estimation." Annals of Human Biology 42, no. 4 (July 4, 2015): 299–301. http://dx.doi.org/10.3109/03014460.2015.1089627.

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Schmeling, A., G. Geserick, W. Reisinger, and A. Olze. "Age estimation." Forensic Science International 165, no. 2-3 (January 2007): 178–81. http://dx.doi.org/10.1016/j.forsciint.2006.05.016.

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Nanjundan, G. "A Note on the Estimation of the Age of a Galton-Watson Process." Mapana - Journal of Sciences 2, no. 1 (November 6, 2003): 38–42. http://dx.doi.org/10.12723/mjs.3.4.

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Nayak, Dr Shruti D., Dr Renjith George, Dr Amarnath Shenoy, and Dr B. Shivapathasundaram Dr. B. Shivapathasundaram. "Age Estimation in Forensic Dentistry- A Review." International Journal of Scientific Research 3, no. 4 (June 1, 2012): 333–38. http://dx.doi.org/10.15373/22778179/apr2014/117.

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Zhang, Huiying, Xin Geng, Yu Zhang, and Fanyong Cheng. "Recurrent age estimation." Pattern Recognition Letters 125 (July 2019): 271–77. http://dx.doi.org/10.1016/j.patrec.2019.05.002.

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Lanitis, Andreas. "Facial Age Estimation." Scholarpedia 5, no. 1 (2010): 9701. http://dx.doi.org/10.4249/scholarpedia.9701.

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Verma, Vivek, Dilip C. Nath, and S. N. Dwivedi. "Bayesian estimation of fertility rates under imperfect age reporting." Statistics in Transition new series 24, no. 2 (March 15, 2023): 39–57. http://dx.doi.org/10.59170/stattrans-2023-019.

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This article outlines the application of the Bayesian method of parameter estimation to situations where the probability of age misreporting is high, leading to transfers of an individual from one age group to another. An essential requirement for Bayesian estimation is prior distribution, derived for both perfect and imperfect age reporting. As an alternative to the Bayesian methodology, a classical estimator based on the maximum likelihood principle has also been discussed. Here, the age misreporting probability matrix has been constructed using a performance indicator, which incorporates the relative performance of estimators based on age when reported correctly instead of misreporting. The initial guess of performance indicators can either be empirically or theoretically derived. The method has been illustrated by using data on Empowered Action Group (EAG) states of India from National Family Health Survey-3 (2005–2006) to estimate the total marital fertility rates. The present study reveals through both a simulation and real-life set-up that the Bayesian estimation method has been more promising and reliable in estimating fertility rates, even in situations where age misreporting is higher than in case of classical maximum likelihood estimates.
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Kimura, Kunihiko. "Estimation of age at death from second metacarpals." Zeitschrift für Morphologie und Anthropologie 79, no. 2 (October 30, 1992): 169–81. http://dx.doi.org/10.1127/zma/79/1992/169.

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Hu, Zhenzhen, Yonggang Wen, Jianfeng Wang, Meng Wang, Richang Hong, and Shuicheng Yan. "Facial Age Estimation With Age Difference." IEEE Transactions on Image Processing 26, no. 7 (July 2017): 3087–97. http://dx.doi.org/10.1109/tip.2016.2633868.

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Dissertations / Theses on the topic "Age estimation"

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Khan, Muhammad Aurangzeb. "Automatic facial age estimation." Thesis, Lancaster University, 2015. http://eprints.lancs.ac.uk/76420/.

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The reliability of automatically estimating human ages, by processing input facial images, has generally been found to be poor. On other hand, various real world applications, often relating to safety and security, depend on an accurate estimate of a person’s age. In such situations, Face Image based Automatic Age Estimation (FI-AAE) systems which are more reliable and may ideally surpass human ability, are of importance as and represent a critical pre-requisite technology. Unfortunately, in terms of estimation accuracy and thus performance, contemporary FI-AAE systems are impeded by challenges which exist in both of the two major FI-AAE processing phases i.e. i) Age based feature extraction and representation and ii) Age group classification. Challenges in the former phase arise because facial shape and texture change independently and the magnitude of these changes vary during the different stages of a person’s life. Additionally, contemporary schemes struggle to exploit age group specific characteristics of these features, which in turn has a detrimental effect on overall system performance. Furthermore misclassification errors which occur in the second processing phase and are caused by the smooth inter-class variations often observed between adjacent age groups, pose another major challenge and are responsible for low overall FI-AAE performance. In this thesis a novel Multi-Level Age Estimation (ML-AE) framework is proposed that addresses the aforementioned challenges and improves upon state-of-the-art FI-AAE system performance. The proposed ML-AE is a hierarchical classification scheme that maximizes and then exploits inter-class variation among different age groups at each level of the hierarchy. Furthermore, the proposed scheme exploits age based discriminating information taken from two different cues (i.e. facial shape and texture) at the decision level which improves age estimation results. During the process of achieving our main objective of age estimation, this research work also contributes to two associated image processing/analysis areas: i) Face image modeling and synthesis; a process of representing face image data with a low dimensionality set of parameters. This is considered as precursor to every face image based age estimation system and has been studied in this thesis within the context of image face recognition ii) measuring face image data variability that can help in representing/ranking different face image datasets according to their classification difficulty level. Thus a variability measure is proposed that can also be used to predict the classification performance of a given face recognition system operating upon a particular input face dataset. Experimental results based on well-known face image datasets revealed the superior performance of our proposed face analysis, synthesis and face image based age classification methodologies, as compared to that obtained from conventional schemes.
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Danielsson, Oscar. "Multimodal Brain Age Estimation." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281834.

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Machine learning models trained on MRI brain scans of healthy subjects can be used to predict age. Accurate estimation of brain age is important for reliably detecting abnormal aging in the brain. One way to increase the accuracy of predicted brain age is through using multimodal data. Previous research using multimodal data has largely been non-deep learning-based; in this thesis, we examine a deep learning model that can effectively utilize several modalities. Three baseline models were trained. Two used T1-weighted and T2- weighted data, respectively. The third model was trained on both T1- and T2- weighted data using high-level fusion. We found that using multimodal data reduced the mean absolute error of predicted ages. Afourth model utilized disentanglement to create a representation robust to missing T1- or T2-weighted data. Our results showed that this model performed similarly to the baselines, meaning that it is robust to missing data and at no significant cost of prediction accuracy.
Maskininlärningsmodeller tränade på MR-data av friska personer kan användas för att estimera ålder. Noggrann uppskattning hjärnans ålder är viktigt för att pålitligt upptäcka onormalt åldrande av hjärnan. Ett sätt att öka noggrannheten är genom att använda multimodal data. Tidigare forskning gjord med multimodal data har till stor del inte varit baserad på djupinlärning; i detta examensarbete undersöker vi en djupinlärningsmodell som effektivt kan utnyttja flera modaliteter. Tre basmodeller tränades. Två använde T1-viktad respektive T2-viktad data. Den tredje modellen tränades på både T1- och T2-viktad data genom högnivå-fusion. Vi fann att användning av multimodal data minskade det genomsnittliga absoluta felet för estimerade åldrar. En fjärde modell använde separering (eng. disentanglement) för att skapa en representation som är robust vid avsaknad av T1- eller T2-viktad data. Resultaten var lika för denna modell och basmodellerna, vilket innebär att modellen är robust mot avsaknad av data, utan någon betydande försämring i noggranhet.
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Buckberry, Jo, and M. Brickley. "Estimation of juvenile age at death." CIFA, 2018. http://hdl.handle.net/10454/17519.

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CASTRO, JOSE DAVID BERMUDEZ. "AGE ESTIMATION FROM FACIALS IMAGES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=25755@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
Esta dissertação tem por objetivo investigar métodos de estimação da idade a partir de imagens faciais. Avalia-se o impacto de distintos fatores sobre a acurácia da estimativa, especificamente, a acurácia da localização de pontos fiduciais, métodos de extração de atributos, de redução de dimensionalidade, e técnicas de regressão. Adicionalmente, foi estudada a influência da raça e do sexo na acurácia da estimação da idade desenvolvido. Consideraram-se cinco métricas de desempenho do sistema, especificamente, o erro médio absoluto (MAE), o erro médio absoluto por década (MAE/D), o erro médio absoluto por idade (MAE/A), o escore acumulado (CS), e os intervalos de confiança (IC). Os experimentos foram realizados empregando dois bancos de dados públicos, cujas imagens estão rotuladas com a idade da face. Os resultados indicaram que o método automático para detecção de pontos fiduciais da face tem uma repercussão moderada sobre a acurácia das estimativas. Entre as variantes analisadas, a que apresentou a melhor acurácia foi o sistema que emprega os AAMs (Active Appearance Models) como método de extração de atributos, o PCA (Principal Components Analysis) como método para reduzir dimensionalidade, e as SVRs (Support Vector Regression) como técnica para fazer regressão.
This thesis aims to investigate methods for age estimation from facial images. The impact of distinct factors over the estimate’s accuracy is assessed, specifically the accuracy in the location of face fiducial points, feature extraction and dimensionality reduction methods, and regression techniques. Additionally, the dependence on race and gender in the accuracy of age estimation is assessed. Five performance metrics have been considered: the mean absolute error (MAE), the mean absolute error per decade (MAE / D), the mean absolute error for age (MAE / A), the cumulative score (CS) and confidence intervals (CI). The experiments were performed using two public databases, whose images are labeled with the age of the face. The results showed the impact of the automatic method for detection of fiducial points of the face has a moderate impact on the accuracy of the estimates. Among the analyzed variants, the one with the best accuracy was the system that employs the Active Appearance Models (AAMs) as feature extraction method, the Principal Components Analysis (PCA) as dimensionality reduction method, and Support Vector Regression (SVRs) as a technique to do regression.
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Heydenrych, Matthew James. "Epigenetic age estimation of cetaceans." Thesis, Curtin University, 2021. http://hdl.handle.net/20.500.11937/84801.

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Age is an important biological parameter which can be used to guide conservation. It is difficult to assess in wild populations, however, and especially in many cetacean species. Epigenetic analyses now offer an alternative for age estimation. In this thesis, I identified the benefits and considerations of epigenetic age estimators for cetaceans, developed a novel high-throughput sequencing workflow for homology-based epigenetic analyses, and successfully built age estimation assays for both sperm and Southern right whales.
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Wu, Yang-Huang. "Sequential estimation of age replacement policies." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA226614.

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Thesis (M.S. in Operations Research)-- Naval Postgraduate School, March 1990.
Thesis Advisor(s): Whitaker, Lyn R. Second Reader: Esary, James D. "March 1990." Description based on signature page as viewed on August 26, 2009. Author(s) subject terms: Sequential Estimation Procedure, Age Replacement Policy, Optimal Replacement, Preventive Maintenance. Includes bibliographical references (p. 54-55). Also available online.
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Ng, Choon Ching. "Face age estimation using wrinkle patterns." Thesis, Manchester Metropolitan University, 2015. http://e-space.mmu.ac.uk/595499/.

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Face age estimation is a challenging problem due to the variation of craniofacial growth, skin texture, gender and race. With recent growth in face age estimation research, wrinkles received attention from a number of research, as it is generally perceived as aging feature and soft biometric for person identification. In a face image, wrinkle is a discontinuous and arbitrary line pattern that varies in different face regions and subjects. Existing wrinkle detection algorithms and wrinkle-based features are not robust for face age estimation. They are either weakly represented or not validated against the ground truth. The primary aim of this thesis is to develop a robust wrinkle detection method and construct novel wrinkle-based methods for face age estimation. First, Hybrid Hessian Filter (HHF) is proposed to segment the wrinkles using the directional gradient and a ridge-valley Gaussian kernel. Second, Hessian Line Tracking (HLT) is proposed for wrinkle detection by exploring the wrinkle connectivity of surrounding pixels using a cross-sectional profile. Experimental results showed that HLT outperforms other wrinkle detection algorithms with an accuracy of 84% and 79% on the datasets of FORERUS and FORERET while HHF achieves 77% and 49%, respectively. Third, Multi-scale Wrinkle Patterns (MWP) is proposed as a novel feature representation for face age estimation using the wrinkle location, intensity and density. Fourth, Hybrid Aging Patterns (HAP) is proposed as a hybrid pattern for face age estimation using Facial Appearance Model (FAM) and MWP. Fifth, Multi-layer Age Regression (MAR) is proposed as a hierarchical model in complementary of FAM and MWP for face age estimation. For performance assessment of age estimation, four datasets namely FGNET, MORPH, FERET and PAL with different age ranges and sample sizes are used as benchmarks. Results showed that MAR achieves the lowest Mean Absolute Error (MAE) of 3.00 ( 4.14) on FERET and HAP scores a comparable MAE of 3.02 ( 2.92) as state of the art. In conclusion, wrinkles are important features and the uniqueness of this pattern should be considered in developing a robust model for face age estimation.
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Dissanayake, Lekamlage Dilukshi Charitha Subashini Dissanayake, and Fabia Afzal. "AI-based Age Estimation from Mammograms." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20108.

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Background: Age estimation has attracted attention because of its various clinical and medical applications. There are many studies on human age estimation from biomedical images such as X-ray images, MRI, facial images, dental images etc. However, there is no research done on mammograms for age estimation. Therefore, in our research, we focus on age estimation from mammogram images. Objectives: The purpose of this study is to make an AI-based model for estimating age from mammogram images based on the pectoral muscle segment and check its accuracy. At first, we segment the pectoral muscle from mammograms. Then we extract deep learning features and handcrafted features from the pectoral muscle segment as well as other regions for comparison. From these features, we built models to estimate the age. Methods: We have selected an experiment method to answer our research question. We have used the U-net model for pectoral muscle segmentation. After that, we have extracted handcrafted features and deep learning features from pectoral muscle using ResNet-50 and Xception. Then we trained Support Vector Regression and Random Forest models to estimate the age based on the pectoral muscle of mammograms. Finally, we observed how accurately these models are in estimating the age by comparing the MSE and MAE values. We have considered breast region (BR) and the whole MLO to answer our research question. Results: The MAE values for both SVR and RF models from handcrafted features is around 10 in years in all cases. On the other hand, with deep learning features MAE is less as compared to handcrafted features. In our experiment, the least observed error value for MAE was around 8.4656 years for the model that extracted the features from the whole MLO using ResNet50 and SVR as the regression model. Conclusions: We have concluded that the breast region (BR) is more accurate in estimating the age compared to PM by having least MAE and MSE values in its models. Moreover, we were able to observe that handcrafted feature models are not as accurate as deep feature models in estimating the age from mammograms.
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Hackman, S. Lucina M. R. "Age estimation in the living : a test of 6 radiographic methods." Thesis, University of Dundee, 2012. https://discovery.dundee.ac.uk/en/studentTheses/b8281974-f44c-444d-b958-001ccfea451f.

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There is a growing recognition that there is a requirement for methods of age estimation of the living to be rigorously tested to ensure that they are accurate, reliable and valid for use in forensic and humanitarian age estimation. The necessity for accurate and reliable methods of age estimation are driven both by humanitarian, political and judicial need. Age estimation methods commonly in use today are based on the application of reference standards, known as atlases, which were developed using data collected from children who participated in longitudinal studies in the early to mid-1900s. The standards were originally developed to provide a baseline to which radiographs could be compared in order to assess the child’s stage of skeletal development in relation to their chronological age, a purpose for which they are still utilised in the medical community. These atlases provide a testable link between skeletal age and chronological age which has been recognised by forensic practitioners who have essentially hijacked this medical capability and applied it to their fields. This has resulted in an increased use of these standards as a method of predicting the chronological age from the skeletal age of a child when the former is unknown. This novel use of the atlases on populations who are distinct, ethnically, temporally and geographically, from those whose data was gathered and was used in the design of the standard leaves the forensic outcomes vulnerable to challenge in court. This study aims to examine the reliability and accuracy of these standards in relation to a modern population, providing a sound statistical base for the use of these standards for forensic purposes. Radiographs were collected from the local hospital from children who had been X-rayed for investigation during attendance at the local A&E department. Four body areas were selected for investigation; the hand-wrist, the elbow, the knee and the foot-ankle and tests were undertaken to assess the radiographs using six commonly uses methods of age estimation. Further images of the wrist and elbow were collected from children in New Delhi, India. These images were subject to age estimation utilising the methods described.
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Kemp, Bryn. "Gestational age estimation in resource poor settings." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:d9ce6416-c6b6-4c06-9992-90ddeaec14e7.

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Background and objectives: The incidence of preterm birth (PTB), and the extent to which it results in perinatal mortality in sub-Saharan Africa (sSA) is unclear, partly because reliable estimates of gestational age (GA) at birth are lacking. This research: 1) Describes how clinical and ultrasound (US) estimates of gestational age (GA) influence PTB rates and perinatal mortality amongst a population in Kilifi, Kenya; 2) Implements a novel PTB classification system as proof of concept that such systems are feasible in low-income settings, and 3) Presents two novel approaches for estimating GA for women presenting >24 weeks’ gestation. Methods: Objectives 1) and 2) used a perinatal surveillance platform developed at the KEMRI/Wellcome Trust Research Programme in Kilifi, Kenya. Ultrasound (US) was offered for GA estimation in women ≤24 weeks’ gestation clinically. To achieve objective 3), two candidate US dating equations were derived by combining a machine learning algorithm with polynomial regression analyses. Lastly, an entirely automated model with the capacity to estimate GA using computational image analysis of the fetal cerebral cortex was developed and tested. Results: 1) Between November 2011 and July 2013, 3630 women presented for antenatal care, 1107 women had US and data were available for 950 (86%) of these. The PTB rate by US (US-GA) was 10.0% compared to 17.1% by a best clinical estimate of GA (C-GA), although the number of perinatal deaths that were preterm by US and C-GA were similar; 2) Implementation of a novel PTB classification system is feasible, and 3) New dating equations and an automated model provide estimates in the 3rd trimester with a prediction error at 34 weeks of 12.4 and 14.2 days, respectively. Conclusion: Clinical estimates of GA significantly overestimate the rate of PTBs. Despite this, the proportion of perinatal deaths in those identified as preterm by clinical and US methods was similar, suggesting that US may be a better predictor of PTB and its associated mortality. Novel dating methods can estimate GA at 34 weeks’ gestation with an error equivalent to that provided by routine clinical methods at 22 weeks’. This has important implications and may extend capacity to provide GA estimates amongst a large group of women whose birth phenotypes remain poorly described.
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Books on the topic "Age estimation"

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Black, Sue, Jason Payne-James, and Anil Aggrawal, eds. Age Estimation in the Living. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470669785.

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Age estimation of the human skeleton. Springfield, Ill: Charles C. Thomas Publisher, Ltd., 2010.

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Gwen, Robbins, and University of Allahabad. Dept. of Ancient History, Culture, and Archaeology., eds. Mesolithic Damdama, dental histology and age estimation. Allahabad: Dept. of Ancient History, Culture & Archaeology, University of Allahabad, 2003.

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Anil, Aggrawal, and Payne-James Jason, eds. Age estimation in the living: The practitioners guide. Hoboken, N.J: John Wiley & Sons Inc., 2011.

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Chesher, Andrew. Diet revealed?: Semiparametric estimation of nutrient intake-age relationships. Bristol: University of Bristol, Department of Economics, 1996.

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Gruber, Jonathan. Social security programs and retirement around the world: Micro estimation. Cambridge, Mass: National Bureau of Economic Research, 2002.

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Pumpiched, Patchara. Sequential estimation of optimal age replacement policies when distribution of lifetimes is phase type. Monterey, Calif: Naval Postgraduate School, 1992.

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Brochu, Melanie Louise. A comparison of two methods for age at death estimation by occlusal tooth wear. Sudbury, Ont: Laurentian University, Department of Biology, 2002.

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Burr, John M. Evaluations of introduced lake trout in the Tanana drainage, and estimation of mortality using maximum age analysis. Anchorage, Alaska: Alaska Dept. of Fish and Game, Division of Sport Fish, 1993.

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Accuracy and precision in some dental radiographic methods: A methodological study with special considerations in age estimation in juveniles. Stockholm: Kongl. Carolinska Medico Chirurgiska Institutet, 1995.

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Book chapters on the topic "Age estimation"

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Black, Sue. "Age Estimation." In Encyclopedia of Global Archaeology, 72–75. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-30018-0_141.

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Black, Sue. "Age Estimation." In Encyclopedia of Global Archaeology, 1–4. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51726-1_141-2.

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Guo, Guodong. "Age Estimation." In Encyclopedia of Biometrics, 1–7. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_9216-1.

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Black, Sue. "Age Estimation." In Encyclopedia of Global Archaeology, 56–59. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4419-0465-2_141.

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Rötzscher, Klaus. "Age Estimation." In Forensic and Legal Dentistry, 195–214. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01330-5_19.

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Guo, Guodong. "Age Estimation." In Encyclopedia of Biometrics, 9–14. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_9216.

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Rai, Balwant, and Jasdeep Kaur. "Dental Age Estimation." In Evidence-Based Forensic Dentistry, 35–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28994-1_3.

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Cameron, Noël, and Laura L. Jones. "Growth, Maturation and Age." In Age Estimation in the Living, 95–129. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470669785.ch7.

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Black, Sue, and George Maat. "Principles of Physical Age Estimation." In Age Estimation in the Living, 77–94. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470669785.ch6.

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Hackman, S. Lucina, Alanah Buck, and Sue Black. "Age Evaluation from the Skeleton." In Age Estimation in the Living, 202–35. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470669785.ch11.

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Conference papers on the topic "Age estimation"

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Rathore, Shweta Singh, and Smriti Sehgal. "Human age estimation using AGES pattern." In 2016 6th International Conference - Cloud System and Big Data Engineering (Confluence). IEEE, 2016. http://dx.doi.org/10.1109/confluence.2016.7508174.

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Alnajar, Fares, Zhongyu Lou, Jose Alvarez, and Theo Gevers. "Expression-Invariant Age Estimation." In British Machine Vision Conference 2014. British Machine Vision Association, 2014. http://dx.doi.org/10.5244/c.28.14.

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Huo, Zengwei, Xu Yang, Chao Xing, Ying Zhou, Peng Hou, Jiaqi Lv, and Xin Geng. "Deep Age Distribution Learning for Apparent Age Estimation." In 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2016. http://dx.doi.org/10.1109/cvprw.2016.95.

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Moreira, Danilo Coura, Eanes Torres Pereira, and Marco Alvarez. "Improving Real Age Estimation from Apparent Age Data." In 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9533308.

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Hironobu Fukai, Hironori Takimoto, Yasue Mitsukura, and Minoru Fukumi. "Apparent age estimation system based on age perception." In SICE Annual Conference 2007. IEEE, 2007. http://dx.doi.org/10.1109/sice.2007.4421466.

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Ng, Choon-Ching, Yi-Tseng Cheng, Gee-Sern Hsu, and Moi Hoon Yap. "Multi-layer age regression for face age estimation." In 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA). IEEE, 2017. http://dx.doi.org/10.23919/mva.2017.7986859.

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Lu, Jiwen, and Yap-Peng Tan. "Gait-based human age estimation." In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495473.

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Zheng, Tianyue, Weihong Deng, and Jiani Hu. "Deep probabilities for age estimation." In 2017 IEEE Visual Communications and Image Processing (VCIP). IEEE, 2017. http://dx.doi.org/10.1109/vcip.2017.8305123.

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Selvi, V. Tamil, and K. Vani. "Age estimation system using MPCA." In 2011 International Conference on Recent Trends in Information Technology (ICRTIT). IEEE, 2011. http://dx.doi.org/10.1109/icrtit.2011.5972319.

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Katiyar, Gauri, Saumya Priya, Vivek Singh, Varsha Shaw, Yash Mathur, and Vikash Gupta. "Face Age Estimation: A Survey." In 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2022. http://dx.doi.org/10.1109/icacite53722.2022.9823726.

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Reports on the topic "Age estimation"

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Bloom, David. On the Nature and Estimation of Age. Period, and Cohort Effects in Demographic Data. Cambridge, MA: National Bureau of Economic Research, September 1985. http://dx.doi.org/10.3386/w1700.

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Payne, Krista. Median Age at First Marriage, 2019. National Center for Family and Marriage Research, May 2021. http://dx.doi.org/10.25035/ncfmr/fp-21-12.

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The median age at first marriage in the United States has increased steadily since the mid-20th century. In the mid-1950s, the median age was at a record low of just over 20 for women and 22 for men, but by 2020, the median age was 28 for women and 30 for men (see Figure 1). The median age at first marriage has increased similarly for both men and women. Consequently, the gender gap in the median age at first marriage has persisted, fluctuating between 1.6 and 2.7 years. This profile uses data from the 2019 American Community Survey (ACS), 1-year estimates to track the trends in women’s and men’s median ages at first marriage. The ACS is ideal because it provides the best annual data on marital status and demographic characteristics allowing for direct estimation of the median age at first marriage (Simmons & Dye, 2004). This is an update to our previous profiles on the topic for the years 2017 (FP-19-06), 2014 (FP-16-07), 2013 (FP-15-05), 2010 (FP-12-07), and 2008 (FP-09-03).
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Balani, Suman, Hetashvi Sudani, Sonali Nawghare, and Nitin Kulkarni. ESTIMATION OF FETAL WEIGHT BY CLINICAL METHOD, ULTRASONOGRAPHY AND ITS CORRELATION WITH ACTUAL BIRTH WEIGHT IN TERM PREGNANCY. World Wide Journals, February 2023. http://dx.doi.org/10.36106/ijar/6907486.

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Introduction: The Accurate estimation of foetal weight is of paramount importance in modern obstetrics for management of labour and delivery. During the past two decades estimated foetal weight is incorporated into the standard routine antepartum evaluation of high-risk pregnancy & deliveries. Present study was conducted to estimation fetal weight by clinical method and by ultrasonography and to nd out its correlation with actual birth weight in term pregnancy. The cross-sectional Material and Methods: observational study was conducted in outpatient or inpatient Obstetric section of Department of Obstetrics & Gynaecology and USG section of Department of Radio-diagnosis of A.C.P.M. Medical College and Hospital, Dhule, Maharashtra. Most of the study Observations & Results: subjects were between 24-28 years of age 53.5% with mean age of 24.71 years. The mean Hadlock weight was 2705 ± 469 gm, while the actual birth weight was 2805 ± 465 gm. The difference was found to be statistically signicant (p<0.05). The difference in Dare's clinical method was found to be 73.3 ± 49.8 gm, while the Hadlock difference was found to be 103.1 ± 77.4 gm. There was a very strong, positive, statistically signicant correlation seen between Dare Weight and Actual Weight (p<0.05). There was a very strong, positive, statistically signicant correlation seen between Hadlock Weight and Actual Weight (p<0.05). Thus, major ndi Conclusion: ng from this study is that clinical estimation of fetal weight is as accurate as the ultrasonographic method of estimation within the normal birth weight range. Our study has important implication as in developing country like India, where ultrasound is not available in many health care delivery systems specially in rural areas where clinical method is easy, cost effective, simple, accurate and can be used even by midwives.
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Flici, Farid, and Nacer-Eddine Hammouda. Mortality evolution in Algeria: What can we learn about data quality? Verlag der Österreichischen Akademie der Wissenschaften, August 2021. http://dx.doi.org/10.1553/populationyearbook2021.res1.3.

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Mortality in Algeria has declined significantly since the country declared its independence in 1962. This trend has been accompanied by improvements in data quality and changes in estimation methodology, both of which are scarcely documented, and may distort the natural evolution of mortality as reported in official statistics. In this paper, our aim is to detect these methodological and data quality changes by means of the visual inspection of mortality surfaces, which represent the evolution of mortality rates, mortality improvement rates and the male-female mortality ratio over age and time. Data quality problems are clearly visible during the 1977–1982 period. The quality of mortality data has improved after 1983, and even further since the population census of 1998, which coincided with the end of the civil war. Additional inexplicable patterns have also been detected, such as a changing mortality age pattern during the period before 1983, and a changing pattern of excess female mortality at reproductive ages, which suddenly appears in 1983 and disappears in 1992.
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Serneels, Pieter, and Stefan Dercon. Aspirations, Poverty and Education: Evidence from India. Research on Improving Systems of Education (RISE), October 2020. http://dx.doi.org/10.35489/bsg-rise-wp_2020/053.

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This paper investigates whether aspirations matter for education, which offers a common route out of poverty. We find that mother aspirations are strongly related to the child’s grade achieved at age 18. The relation is nonlinear, suggesting there is a threshold, and depends on caste, household income and the village setting. The coefficients remain large and significant when applying control function estimation, using firstborn son as instrument. A similar strong relation is observed with learning outcomes, including local language, English and maths test results, and with attending school, but not with attending private education. These results are confirmed for outcomes at age 15. The findings provide direct evidence on the contribution of mother aspirations to children’s education outcomes and point to aspirations as a channel of intergenerational mobility. They suggest that education outcomes can be improved more rapidly by taking aspirations into account when targeting education programmes, and through interventions that shape aspirations.
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Kotlikoff, Laurence. Estimating The Age-Productivity Profile Using Lifetime Earnings. Cambridge, MA: National Bureau of Economic Research, December 1988. http://dx.doi.org/10.3386/w2788.

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Zeng, Yi, Eric Stallard, and Zhenglian Wang. Estimating age-status-specific demographic rates that are consistent with the projected summary measures in family households projection. Rostock: Max Planck Institute for Demographic Research, August 2002. http://dx.doi.org/10.4054/mpidr-wp-2002-033.

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Tamburini, Andrea, Arkadiusz Wiśniowski, and Dilek Yildiz. BAYESIAN MULTI-DIMENSIONAL MORTALITY RECONSTRUCTION. Verlag der Österreichischen Akademie der Wissenschaften, January 2024. http://dx.doi.org/10.1553/0x003eb05e.

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Even though mortality differentials by socio-economic status and educational attainment level have been widely examined, this research is often limited to developed countries and recent years. This is primarily due to the absence of consistently good-quality inherent data. Systematic studies with a broad geographical and temporal spectrum that engage with the link between educational attainment and mortality are lacking. In this paper, we propose a mortality rates reconstruction model based on multiple patchy data sources, and provide mortality rates by level of education. The proposed model is a hierarchical Bayesian model that combines the strengths of multiple sources in order to disaggregate mortality rates by time periods, age groups, sex and educational attainment. We apply the model in a case study that includes 13 countries across South-East Europe, Western Asia and North Africa, and calculate education-specific mortality rates for five-year age groups starting at age 15 for the 1980-2015 time period. Furthermore, we evaluate the model’s performance relying on standard convergence indicators and trace plots, and validate our estimates via posterior predictive checks. This study contributes to the literature by proposing a novel methodology to enhance the research on the relationship between education and adult mortality. It addresses the lack of educationspecific mortality differentials by providing a flexible method for their estimation.
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Zyphur, Michael. Instrumental Variable Analysis Using lavaan in R. Instats Inc., 2022. http://dx.doi.org/10.61700/ff0rzg91cv2ku469.

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This seminar introduces the lavaan package in R for estimating causal effects with observational data using instrumental variables in both path analysis and SEM, grounded in introductions to both techniques including CFA. Traditional bootstrapping and Bayesian methods are explored for estimation and hypothesis testing. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent point.
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Zyphur, Michael. Instrumental Variable Analysis using Stata's SEM Command. Instats Inc., 2022. http://dx.doi.org/10.61700/7ukunn6wlwzmh469.

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This seminar introduces the sem command in Stata for estimating causal effects with observational data using instrumental variables in both path analysis and SEM, grounded in introductions to both techniques including CFA. Traditional bootstrapping and Bayesian methods are explored for estimation and hypothesis testing. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent point.
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