Transactions on Pattern Analysis and Machine Intelligence , regular paperA Survey of Machine Learning

This paper describes and evaluates the types of machine learning techniques which are appropriate for the special needs of automatic target recognition. Artiicial neural networks has been the most popular choice. However, they have several shortcomings , including that they do not readily allow the learned domain theory to be revised in response to new conditions, new targets, or new sensors. Recent advances in machine learning for other applications suggest that explanation-based learning and theory revision are promising candidates to overcome these deeciencies. Domain Theory identified target sensor observations feature vector models of targets Figure 1: Components of a typical ATR system.