This paper presents a novel approach to face detection. A potential face pattern is first filtered by a Gaussian derivative filter bank to generate a set of derivative images, which are then transformed by the Angular Radial Transform (ART) to form a compact set of representation feature vectors. Using these feature vectors for face detection is based on a two level multiple support vector mach...

Until recently, the alveolar region could not be investigated in-vivo. A novel technique, based on confocal microscopy, can now provide new images of the respiratory alveolar system, for which quantitative analysis tools must be developed, for diagnosis and follow up of pathological situations. In particular, we wish to aid the clinician by developing a computer-aided diagnosis system, able to ...

Mars probes send back to Earth enormous amount of data. Automating the analysis of this data and its interpretation represents a challenging test of significant benefit to the domain of planetary science. In this study, we propose combining terrain segmentation and classification to interpret Martian topography data and to identify constituent landforms of the Martian landscape. Our approach us...

In this paper, we introduce a SAR images target recognition approach based on the contourlet transform and support vector machine (SVM), which takes technological advantages of both SVM and the contourlet transform for feature extraction.

Text in video is a very compact and accurate clue for video indexing and summarization. This paper presents an algorithm regarding word group as a special symbol to detect, localize and extract video text using support vector machine (SVM) automatically. First, four sobel operators are applied to get the EM(edge map) of the video frame and the EM is segmented into N×2N size blocks. Then charact...

The identity of musical instruments is reflected in the acoustic attributes of musical notes played with them. Recently, it has been argued that these characteristics of musical identity (or timbre) can be best captured through an analysis that encompasses both time and frequency domains; with a focus on the modulations or changes in the signal in the spectrotemporal space. This representation ...

In this paper, we consider the problem of sentence difficulty analysis from various angles. Past works have endeavored to design deterministic scoring algorithms depending only on semantic and syntactic information. We propose instead not only to hire local feature space representing individual sentence with its syntactic and semantic structure, but also to consider global distributional differ...

Authors of short papers such as letters or editorials often express complementary opinions, and sometimes contradictory ones, on related work in previously published articles. The MEDLINE® citations for such short papers are required to list bibliographic data on these “commented on” articles in a “CON” field. The challenge is to automatically identify the CON articles referred to by the author...

The success of support vector machines (SVMs) for classification problems is often dependent on an appropriate normalization of the input feature space. This is particularly true in topic identification, where the relative contribution of the common but uninformative function words can overpower the contribution of the rare but informative content words in the SVM kernel function score if the f...

We consider the distortion measure in vector quantization based speaker identification system. The model of a speaker is a codebook generated from the set of feature vectors from the speakers voice sample. The matching is performed by evaluating the distortions between the unknown speech sample and the models in the speaker database. In this paper, we introduce a weighted distortion measure tha...