A Universal Machine-Learning-Based Automated Testing System for Consumer Electronic Products

An intelligent fuzzy-based recommendation system for consumer electronic products

Developing an intelligent recommendation system is a good way to overcome the problem of overloaded products information provided by the e-commerce enterprises. As there are a great number of products on the Internet, it is impossible to recommend all kinds of products in one system. We believe that the personalized recommendation system should be built up according to the special features of a...

color detection system for agricultural products based on electronic vision

development of a suitable method for color sorting of agricultural products such as: tomato, apple and orange, based on surface reflection and image formation was the goal of this research. a suitable scheme of color differentiation using an optic head and electrical processing circuitry for separating red from green and other colors is presented. a photo-conductive transducer, electrical resis...

A Machine Learning System for Automated Whole-Brain Seizure Detection

Epilepsy is a chronic neurological condition that affects approximately 70 million people worldwide. Characterised by sudden bursts of excess electricity in the brain, manifesting as seizures, epilepsy is still not well understood when compared with other neurological disorders. Seizures often happen unexpectedly and attempting to predict them has been a research topic for the last 30 years. El...

Machine Learning for Automated Reasoning

Sports Commentary Recommendation System (SCoReS): Machine Learning for Automated Narrative

Automated sports commentary is a form of automated narrative. Sports commentary exists to keep the viewer informed and entertained. One way to entertain the viewer is by telling brief stories relevant to the game in progress. We introduce a system called the Sports Commentary Recommendation System (SCoReS) that can automatically suggest stories for commentators to tell during games. Through sev...