A Whistle-Stop Tour Through Object Detection Using AI
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Join academic experts from Sheffield Hallam University for a whistle-stop tour through object detection using AI.
Object detection in complex real-world scenes is widely regarded as one of the most challenging problems in computer vision. Object detection has recently started to gain a lot of interest – predominantly as a key technology in self-driving cars, allowing the vehicle to identify pedestrians, driving lanes, other motor vehicles, road signs, or obstructions in the road. Although various machine learning methods (such as the Viola-Jones framework and Histogram of Oriented Gradients (HOG)) have been around for the past 20 years or so, it is only recently with advances in deep learning that object detection algorithms have achieved a useful level of accuracy in anything more than niche applications.
Dr Alex Shenfield, Associate Professor in Machine Learning will provide a whistle-stop tour through some recent developments in applying deep learning to object recognition (with imagery and examples), before discussing some current and future applications of these techniques and future research directions.
