INTRODUCTION There is a large class of problems that are at best poorly solved. These problems involve the transformation of data across the boundary between the real world and the digital world. And they occur whenever a computer is sampling and/or acting on real world data. Examples of these “boundary transformation” problems include the computer recognition of human speech, computer vision, ...

Contextual information can often be exploited for improving assisted search and automatic target recognition ATR Previously we re ported on the development of hierarchical pyra mid neural network HPNN algorithms for automatically learning and integrating context for target detection demonstrating the appli cation of these algorithms to the problem of building detection in satellite imagery Spen...

Terminological variation is an integral part of the linguistic ability to realise a concept in many ways, but it is typically considered an obstacle to automatic term recognition (ATR) and term management. We present a method that integrates term variation in a hybrid ATR approach, in which term candidates are recognised by a set of linguistic filters and termhood assignment is based on joint f...

Semi-supervised learning (SSL) in synthetic aperture radars (SAR) is one of the research hotspots field radar-image automatic target recognition (ATR). It can efficiently deal with challenging environments where there are insufficient labeled samples and large unlabeled SAR dataset. In recent years, consistency regularization methods semi-supervised have shown considerable improvement accuracy ...

The wavelet transform gives a compact multiscale representation of a digital image and provides a hierarchical structure which is well suited for post-processing. With its good localization property in both the spatial domain and the frequency domain, wavelet-based image compression has gained a huge success in the past several years. In this paper we present a wavelet-based image codec special...

We propose a novel automatic target recognition (ATR) system for classification of three types of ground vehicles in the MSTAR public release database. First, each image chip is pre-processed by extracting fine and raw feature sets, where raw features compensate for the target pose estimation error that corrupts fine image features. Then, the chips are classified by using the adaptive boosting ...

We propose a novel automatic target recognition (ATR) system for classification of three types of ground vehicles in the MSTAR public release database. First, MSTAR image chips are represented as fine and raw feature vectors, where raw features compensate for the target pose estimation error that corrupts fine image features. Then, the chips are classified by using the adaptive boosting (AdaBoo...

Sun-Gu Sun Hyun Wook Park, MEMBER SPIE Korea Advanced Institute of Science and Technology Department of Electrical Engineering 373-1 Guseong-dong Yuseong-gu, Daejeon 305-701 Korea E-mail: [email protected] Abstract. We propose an automatic target recognition (ATR) algorithm for recognizing nonoccluded and partially occluded military vehicles in natural forward-looking infrared (FLIR) im...