Identification and detection of an object or a feature in a digital image/video using neural networks to filter images/video through a series of artificial neuron layers.
Partitioning an image into sets of pixels to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze.
Browsing, searching and retrieving images from a large database of digital images.
Face and Emotion Recognition
Using feature extraction, subset feature classifier and emotion classifier to recognize faces and emotions.
Generation of textual description from an image based on the objects and their actions in that image
Extraction of the insights from the videos such as faces, scene segmentation, translation, automatic language detection, Keywords extraction, Sentiment analysis etc…
Recognition of a speaker based on measuring the distinctions in individual voices to uniquely identify the speaker
Shortening a text document using Machine Learning to create a summary with the major points of the original document.
Text to Speech
Creating natural-sounding, synthetic human speech from the text using neural network models.
Using natural language processing (NLP) and machine learning techniques to determine whether a piece of writing is positive, negative or neutral.
Text Q&A are powered by rules or artificial intelligence that let people interact via a chat interface.
Mapping text format entities into semantic concept categories with some probabilities. Can help companies in classifying entities.
Highlights keywords in emails using deep learning. Helps companies looking for product complaints or coupons from customer emails.