Have you ever tried to find out somebody?s age without asking directly about it? Forget all the number tricks and let the Artificial Intelligence (AI) do this job for you! It goes without saying that AI can predict accurately your age.
In fact, age, alongside with gender, is one of the fundamental socio-biological qualities that determines human interactions. That?s why a growing number of smart applications, including social media, visual supervision, human computer interaction, access control, and competitive intelligence, are concerned with the importance of making precise age estimations.
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It goes without saying that AI can predict accurately your age.
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2 Types of Automatic Age Prediction
All in all, AI-supported age prediction represents the automatic labeling of an individual?s age group or specific age using information obtained from either facial image-based or text-based datasets.
Facial image-based age prediction stands for the automatic age estimation built upon distinct visual patterns emerging from the facial appearance. Predicting age from the facial images dataset involves two stages:
- Face detection in the input image or video stream.
- Extraction of the face region of interest (ROI) and application of the age detector algorithm to identify the age of the person.
Text-based age prediction, in turn, deals with the automatic extraction of demographic and psychological characteristics of authors from the written text. It presupposes the application of machine learning algorithms to the analysis of the linguistic properties of the given text, including:
- Character n-grams;
- Token n-grams;
- Part-of-speech n-grams;
- Specific token subsets (emoticons, acronyms, function words, LIWC dictionaries);
- Readability features (average word and sentence length count);
- Character-based stylistic features (punctuation, character repetition);
- Extracted topics.