Multi-Stage Feature Constraints Learning for Age Estimation

2020 ◽  
Vol 15 ◽  
pp. 2417-2428 ◽  
Author(s):  
Min Xia ◽  
Xu Zhang ◽  
Wan'an Liu ◽  
Liguo Weng ◽  
Yiqing Xu
Keyword(s):  
Age Estimation ◽  
Multi Stage ◽  
Feature Constraints

scholarly journals Age Estimation Using OLPP Features

2017 ◽  
Vol 10 (1) ◽  
pp. 238-248
Author(s):  
M. S Vaishnavi ◽  
A Vijayalakshmi
Keyword(s):  
Age Estimation ◽  
Binary Classification ◽  
Real Life ◽  
Support Vector ◽  
Vending Machines ◽  
Locality Preservation ◽  
Missing Children ◽  
Multi Stage ◽  
Sobel Edge Detection ◽  
Age Range

Aging face recognition poses as a key difficulty in facial recognition. It refers to identification of a person face over varied ages. It includes issues like age estimation, progression and verification. Non-availability of facial aging databases make it harder for any system to achieve good accuracy as there are no good training sets available. Age estimation when done correctly has a varied number of real life applications like age detailed vending machines, age specific access control and finding missing children. This paper implements age estimation using Park Aging Mind laboratory - Face database that contains metadata and 293 unique images of 293 individuals. Ages range from 19 to 45 with a median age of 32. Race is classified into two categories : African-American and Caucasian giving an accuracy of 98%. Sobel edge detection and Orthogonal locality preservation projection were used as the dominant features for the training and testing of age estimation. A Multi-stage binary classification using support vector machine was used to classify images into an age group thereafter predicting an individual’s age. The effectiveness of this method can be increased by using a large dataset with a wider age range.

scholarly journals SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation

2018 ◽  
Author(s):  
Tsun-Yi Yang ◽  
Yi-Hsuan Huang ◽  
Yen-Yu Lin ◽  
Pi-Cheng Hsiu ◽  
Yung-Yu Chuang
Keyword(s):  
Age Estimation ◽  
Network Architecture ◽  
Dynamic Range ◽  
Single Image ◽  
Input Face ◽  
Multi Stage ◽  
Compact Size ◽  
Model Size ◽  
Multi Class Classification ◽  
Coarse To Fine

This paper presents a novel CNN model called Soft Stagewise Regression Network (SSR-Net) for age estimation from a single image with a compact model size. Inspired by DEX, we address age estimation by performing multi-class classification and then turning classification results into regression by calculating the expected values. SSR-Net takes a coarse-to-fine strategy and performs multi-class classification with multiple stages. Each stage is only responsible for refining the decision of its previous stage for more accurate age estimation. Thus, each stage performs a task with few classes and requires few neurons, greatly reducing the model size. For addressing the quantization issue introduced by grouping ages into classes, SSR-Net assigns a dynamic range to each age class by allowing it to be shifted and scaled according to the input face image. Both the multi-stage strategy and the dynamic range are incorporated into the formulation of soft stagewise regression. A novel network architecture is proposed for carrying out soft stagewise regression. The resultant SSR-Net model is very compact and takes only 0.32 MB. Despite its compact size, SSR-Net’s performance approaches those of the state-of-the-art methods whose model sizes are often more than 1500× larger.

Planning and Search in Multi-Stage Risky Decision Making

2011 ◽  
Author(s):  
Jared Hotaling ◽  
Jerry Busemeyer ◽  
Richard Shiffrin
Keyword(s):  
Decision Making ◽  
Risky Decision Making ◽  
Risky Decision ◽  
Multi Stage

Effects of Cooking Oil Subsidy Removals on Related Markets in Malaysia: A Comparative Static, Multicommodity, Multi Stage Production Approach

2011 ◽  
Author(s):  
Jamal Othman ◽  
Yaghoob Jafari
Keyword(s):  
Equilibrium Model ◽  
Comparative Statics ◽  
Partial Equilibrium ◽  
Cooking Oil ◽  
Multi Stage ◽  
Supply Factor ◽  
Partial Equilibrium Model ◽  
Factor Markets ◽  
Input Markets ◽  
Production Approach

Malaysia is contemplating removal of most of her subsidy support measures including subsidies on cooking oil which is largely palm oil based. This paper aims to examine the effects of cooking oil subsidy removals on the competitiveness of the oil palm subsector and related markets. This is done by developing and applying a comparative static, multi-commodity, partial equilibrium model with multi-stages of production function for the Malaysian perennial crops subsector which explicitly links different stages of production, primary and intermediate input markets, trade, and policy linkages. Results partly suggest that export of cooking oil will increase by 0.2 per cent due to a 10 per cent cooking oil subsidy reduction, while domestic output of cooking oil may eventually see a net decline of 1.97 per cent. The results clearly point out that the effect of reducing cooking oil subsidies is relatively small at the upstream levels and therefore it only induces minute effects on factor markets. Consequently, the market for other agricultural crops is projected to change very marginally.   Keywords: Multicomodity, comparative statics, partial equilibrium model, output supply-factor markets linkages, effects of cooking oil subsidy removals.

IMPACT ASSESSMENT OF AGRICULTURAL TRANSFORMATION PROJECT ON PRODUCTIVITY AND POVERTY AMONG RICE FARMERS IN KANO STATE, NIGERIA.

2020 ◽  
Vol 4 (2) ◽  
pp. 392-400
Author(s):  
O. S. Balogun ◽  
M. A. Damisa ◽  
O. Yusuf ◽  
O. L. Balogun
Keyword(s):  
Sampling Method ◽  
Insect Pests ◽  
Study Data ◽  
Average Treatment Effect ◽  
Descriptive Statistics ◽  
Rice Farmers ◽  
Agricultural Transformation ◽  
Multi Stage ◽  
Significant Difference ◽  
Late Model

The study was carried out to examine the effect of agricultural transformation on the beneficiary’s productivity and poverty of rice farmers in Kano State Nigeria. A multi-stage sampling method was employed to select 571 respondents for the study. Data were collected through structured questionnaires on respondent’s income, input and output quantities as well as their expenditures. Data were analysis using descriptive statistics, Foster-Greer-Thorbecke (FGT), Propensity score matching and LATE model. Results from the study shows that respondents productivity revealed a significant difference of about 127 kg/ha in rice productivity between participants and non-participants. Also, the LATE estimates revealed an average treatment effect ATE0 of about 222.98kg/ha. Furthermore, the project had a significant effect N11, 321.4 on the participant’s consumption expenditure than the non-participants N9980.60. Moreover, participants were, able to increase their household total expenditures by N34780 per annum. Fluctuations of input/output prices insect pests and inadequate extension visits were all the major constraints faced by the farmers. It was recommended that farmers’ information and sensitization system should be overhauled and improved. Also, attention should be given to well organize extension visits for the farmers from stake holders

COMPARISION OF DENTAL SCORING SYSTEM WITH RADIOGRAPHIC SKELETAL SYSTEM IN AGE ESTIMATION

JKCD ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 9-11
Author(s):  
Sadaf Ambreen
Keyword(s):  
Age Estimation ◽  
Scoring System ◽  
Skeletal Age ◽  
Chronological Age ◽  
Age Group ◽  
Dental Age ◽  
Scoring Method ◽  
Cross Sectional ◽  
Study Results ◽  
Male Subjects

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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