Using Tetracycline to Evaluate Age Estimation in a Long‐Lived Aquatic Mammal

Objectives: To compare Demirjian Dental scoring method with Greulich-Pyle (GP) Skeletal method of age estimation in pubertal children. Materials and Methods: Sample of the study included 267 male healthy subjects of 11-16 years of age group.. Demirjian Scoring system was utilized to evaluate the orthopantomograms to assess their Dental age and the Hand-Wrist radiographs were analyzed to calculate the skeletal age by utilizing GP atlas. Chronological age was obtained from the date of birth of the subject .Both methods were compared with one another and with the chronological age. It was a cross-sectional study and only healthy male subjects without any clinical abnormalities were included in the study. Results: A total of 267 male subjects of 11-16 years of age group were assessed by Demirjian and Greulich Pyle Methods. Both were compared with Chronological Age. Data obtained was statistically analyzed and the Student “t” test was applied in the study population. The mean difference between Chronolgical age and dental age was 0.69years and that of chronological age and skeletal age was 0.87 years. It was observed from dental age assessment that it does not differ much from the skeletal age. Conclusion: It was concluded that Demirjian method of Age Estimation is more precise than Greulich Pyle method of Age Estimation. Furthermore both methods can be used selectively in Medicolegal cases to access bone age which can be easily correlated to chronological age.

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Assessing Aquatic Mammal Welfare While Assessing Differing Values and Imperfect Tradeoffs

Aquatic Mammals ◽

10.1578/am.44.2.2018.116 ◽

2018 ◽

Vol 44 (2) ◽

pp. 116-141 ◽

Cited By ~ 2

Author(s):

David S. Miller ◽

Raymond Anthony ◽

Gail Golab

Keyword(s):

Aquatic Mammal

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Analysis of Race and Gender Bias in Deep Age Estimation Models

2020 28th European Signal Processing Conference (EUSIPCO) ◽

10.23919/eusipco47968.2020.9287219 ◽

2021 ◽

Author(s):

Andraz Puc ◽

Vitomir Struc ◽

Klemen Grm

Keyword(s):

Gender Bias ◽

Age Estimation ◽

Race And Gender ◽

And Gender ◽

Estimation Models

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A Review of Different Techniques of Age Estimation from Human Face

SMART MOVES JOURNAL IJOSCIENCE ◽

10.24113/ijoscience.v4i10.163 ◽

2018 ◽

Vol 4 (10) ◽

pp. 6

Author(s):

Khemchandra Patel ◽

Dr. Kamlesh Namdev

Keyword(s):

Age Estimation ◽

Real Life ◽

Extraction Methods ◽

Human Face ◽

Age Changes ◽

Missing Children ◽

Different Types ◽

Age Variation ◽

Human Faces ◽

Facial Age

Age changes cause major variations in the appearance of human faces. Due to many lifestyle factors, it is difficult to precisely predict how individuals may look with advancing years or how they looked with "retreating" years. This paper is a review of age variation methods and techniques, which is useful to capture wanted fugitives, finding missing children, updating employee databases, enhance powerful visual effect in film, television, gaming field. Currently there are many different methods available for age variation. Each has their own advantages and purpose. Because of its real life applications, researchers have shown great interest in automatic facial age estimation. In this paper, different age variation methods with their prospects are reviewed. This paper highlights latest methodologies and feature extraction methods used by researchers to estimate age. Different types of classifiers used in this domain have also been discussed.

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