Age Estimation
71 papers with code • 16 benchmarks • 19 datasets
Age Estimation is the task of estimating the age of a person from an image some other kind of data.
( Image credit: BridgeNet )
Benchmarks
These leaderboards are used to track progress in Age Estimation
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Libraries
Use these libraries to find Age Estimation models and implementations
UTKFace
MORPH
Adience
CACD
FG-NET
AADB
AgeDB
MegaAge
Latest papers with no code
Age Estimation Based on Graph Convolutional Networks and Multi-head Attention Mechanisms
The Graph Convolutional Network (GCN) is used to extract features from irregular face images effectively, and multi-head attention mechanisms are added to avoid redundant features and capture key region information in the image.
Deep Learning based Systems for Crater Detection: A Review
To be specific, we discuss the challenges in crater detection due to the complex properties of the craters and survey the DL-based CDAs by categorizing them into three parts: (a) semantic segmentation-based, (b) object detection-based, and (c) classification-based.
Sex-based Disparities in Brain Aging: A Focus on Parkinson's Disease
PD is linked to faster brain aging.
FaceSkin: A Privacy Preserving Facial skin patch Dataset for multi Attributes classification
Human facial skin images contain abundant textural information that can serve as valuable features for attribute classification, such as age, race, and gender.
General vs. Long-Tailed Age Estimation: An Approach to Kill Two Birds with One Stone
Driven by this, some works suggest that each class should be treated equally to improve performance in tail classes (with a minority of samples), which can be summarized as Long-tailed Age Estimation.
Learning Subjective Time-Series Data via Utopia Label Distribution Approximation
In this work, we propose Utopia Label Distribution Approximation (ULDA) for time-series data, which makes the training label distribution closer to real-world but unknown (utopia) label distribution.
Concurrent ischemic lesion age estimation and segmentation of CT brain using a Transformer-based network
The cornerstone of stroke care is expedient management that varies depending on the time since stroke onset.
Robust Brain Age Estimation via Regression Models and MRI-derived Features
The proposed BAE framework provides a new approach for estimating brain age, which has important implications for the understanding of neurological disorders and age-related brain changes.
SFCNeXt: a simple fully convolutional network for effective brain age estimation with small sample size
Deep neural networks (DNN) have been designed to predict the chronological age of a healthy brain from T1-weighted magnetic resonance images (T1 MRIs), and the predicted brain age could serve as a valuable biomarker for the early detection of development-related or aging-related disorders.
Noise-Tolerance GPU-based Age Estimation Using ResNet-50
In recent years, a person's age has been studied as one of the important features of the face.
