Journal ArticleDOI
Deep Appearance Model and Crow-Sine Cosine Algorithm-Based Deep Belief Network for Age Estimation
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TLDR
The overall process of age estimation is performed using three important steps, where the DBN classifier is trained optimally using the proposed learning algorithm named as crow-sine cosine algorithm (CS).Abstract:
Age estimation has been paid great attention in the field of intelligent surveillance, face recognition, biometrics, etc. In contrast to other facial variations, aging variation presents several unique characteristics, which make age estimation very challenging. The overall process of age estimation is performed using three important steps. In the first step, the pre-processing is performed from the input image based on Viola-Jones algorithm to detect the face region. In the second step, feature extraction is done based on three important features such as local transform directional pattern (LTDP), active appearance model (AAM), and the new feature, deep appearance model (Deep AM). After feature extraction, the classification is carried out based on the extracted features using deep belief network (DBN), where the DBN classifier is trained optimally using the proposed learning algorithm named as crow-sine cosine algorithm (CS).read more
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Journal ArticleDOI
Cloud Intrusion Detection Model Based on Deep Belief Network and Grasshopper Optimization
TL;DR: In this paper , an effective cloud IDS using Grasshopper optimization algorithm (GOA) and deep belief network (DBN) is proposed to solve the issues and to increase the accuracy.
Journal ArticleDOI
A New Hybrid Model to Predict Human Age Estimation from Face Images Based on Supervised Machine Learning Algorithms
TL;DR: In this paper , Pseudo Zernike Moments (PZM), Active Appearance Model (AAM), Bio-Inspired Features (BIF), Support Vector Machine (SVM) and Support Vector Regression (SVR) algorithms are used to predict the age range of face images.
References
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Threshold prediction for segmenting tumour from brain MRI scans
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Adaptive active appearance models
A.U. Batur,Monson H. Hayes +1 more
TL;DR: The idea of a linearly adaptive gradient matrix presented in this paper provides an interesting compromise between a standard optimization technique that recomputes the gradient at every iteration and the fixed gradient matrix approach of the basic AAM.
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Automatic age estimation based on deep learning algorithm
Yuan Dong,Yinan Liu,Shiguo Lian +2 more
TL;DR: A deep learning based framework for age classification task in which face image is assigned to a label that represents an age range, which demonstrates the excellent performance of the proposed algorithm against the state-of-the-art methods.
Journal ArticleDOI
Multi-Stage Feature Constraints Learning for Age Estimation
TL;DR: A multi-stage feature constraints learning method that gradually refines the feature through three feature constraint stages and efficiently merges the features of three stages and optimizes the mapping of feature maps to an ordered binary comparison space is proposed.
Journal ArticleDOI
Local descriptors in application to the aging problem in face recognition
Michał Bereta,Paweł Karczmarek,Paweł Karczmarek,Witold Pedrycz,Witold Pedrycz,Marek Reformat +5 more
TL;DR: This paper quantifies abilities of local descriptors used in face recognition in the context of age discrimination, and presents the results for different age groups and for various age differences of individuals present in the training and testing images.
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