Semi-supervised and unsupervised extensions to maximum-margin structured prediction
Syed Shaukat Raza Abidi · UTS ePRESS (University of Technology Sydney) · 2016
Structured prediction is the backbone of various computer vision and machine learning applications.Inspired by the success of maximum-margin classifiers in the recent years; in this thesis, we will present novel semi-supervised and unsupervised extensions to structured prediction via maximum-margin classifiers.For semi-supervised structured prediction, we have tackled the problem of recognizing actions from single images.Action recognition from a single image is an important task for applications such as image annotation, robotic navigation, video surveillance and several others.We propose approaching action recognition by first