Age Group Classification

Age group classification aims to accurately determine a person's age range using various data modalities, including text, video, handwriting, and brain activity. Current research focuses on developing robust models, such as convolutional neural networks and transformers, that leverage spatio-temporal information and address challenges like data scarcity for older age groups and label ambiguity. These advancements have implications for diverse fields, including healthcare (frailty detection), marketing (targeted advertising), and human-computer interaction (age-appropriate interfaces), by enabling more accurate and nuanced age-related analyses.