In this paper, radar target classification based on Synthetic Aperture Radar (SAR) images is investigated. Different criteria for extracting features from MSTAR data are presented, and classification rates shown, emphasizing where the useful information in terms of recognition resides. The combination of different features is also examined, linking the classification accuracy of the system to t...

An improved processing description to be employed in biosonar signal processing in a cochlea model is proposed and examined. It is compared to conventional models using a modified discrimination analysis and both are tested. Their performances are evaluated with echo data captured from natural targets (trees). Results indicate that the phase characteristics of low-pass filters employed in the e...

Rules are a type of human-understandable knowledge, and rule-based methods are very popular in building decision support systems. However, most current rule based classification systems build small classifiers where no rules account for exceptional instances and a default prediction plays a major role in the prediction. In this paper, we discuss two schemes to build rule based classifiers using...

every society has its own culture, values, and ideology. translations convey the meaning as well as cultural and ideological values, beliefs, ideas and norms from source culture to target culture. one type of translation which nowadays is popular among people, and can attract so many audiences in different ages is audiovisual translation (avt), particularly dubbing. if there is difference betwe...

We consider the problem of classifying micro-posts as churny or non-churny with respect to a given brand. Using Twitter data about three brands, we find that standard machine learning techniques clearly outperform keyword based approaches. However, the three machine learning techniques we employed (linear classification, support vector machines, and logistic regression) do not perform as well o...

Target-dependent sentiment classification remains a challenge: modeling the semantic relatedness of a target with its context words in a sentence. Different context words have different influences on determining the sentiment polarity of a sentence towards the target. Therefore, it is desirable to integrate the connections between target word and context words when building a learning system. I...

UNLABELLED The drug classification scheme of the World Health Organization (WHO) [Anatomical Therapeutic Chemical (ATC)-code] connects chemical classification and therapeutic approach. It is generally accepted that compounds with similar physicochemical properties exhibit similar biological activity. If this hypothesis holds true for drugs, then the ATC-code, the putative medical indication are...

Stochastic resonance has received significant attention recently in the signal processing community with emphasis on signal detection. The basic notion is that the performance of some suboptimal detectors can be improved by adding independent noise to the measured (and already noise contaminated) observation. The notion of adding noise makes sense if the observation is the result of nonlinear p...

This paper describes a real-time system for multi-target tracking and classification in image sequences from a single stationary camera. Several targets can be tracked simultaneously in spite of splits and merges amongst the foreground objects and presence of clutter in the segmentation results. In results we show tracking of upto 17 targets simultaneously. The algorithm combines Kalman filter-...

To recognize underwater target precisely is always a hot potato to navies due to the complicated watery environment. It’s different from the aerial circumstance. There is much more interfere under the sea. Sonar is the most efficient way to detect underwater world at present time. In this paper, a geneticbased classifier system is designed which recognizes targets by sonar fingerprints. This me...