Entity relation extraction is an important task for information extraction, which refers to extracting the relation between two entities from input text. Previous researches usually converted this problem to a sequence labeling problem and used statistical models such as conditional random field model to solve it. This kind of method needs a large, high-quality training dataset. So it has two m...

This paper presents a method of contour extraction and compression from grey level image. The proposed algorithm is applied in spectral domain using single-level wavelet transform (WT). Single step parallel contour extraction (SSPCE) method is used for the binary image after inverse wavelet transform is applied to the details images. Then the contours are compressed using either Ramer or Trapez...

Linear system identification is an important tool in experimental modal analysis. It allows for the extraction of resonance frequencies, damping ratios and mode shapes of a vibrating structure. In general, the model order is chosen quite high so as to catch all the important characteristics of the structure, even in the presence of large amounts of measurement noise. This often results in the a...

submission for Workshop on Solving Computational Challenges in Medical Imaging – July 2007 Targeted Statistical Image Reconstruction for Cardiac CT Imaging Adam Alessio, PhD, [email protected] Department of Radiology University of Washington Purpose: Current computed tomography (CT) systems generate images with analytic tomographic reconstruction methods because they are simple to imple...

Nonnegative matrix factorization (NMF) has been successfully used in many fields as a low-dimensional representation method. Projective nonnegative matrix factorization (PNMF) is a variant of NMF that was proposed to learn a subspace for feature extraction. However, both original NMF and PNMF are sensitive to noise and are unsuitable for feature extraction if data is grossly corrupted. In order...

In the panoramic camera image there is serious noise interference, and it is not easy to extract and other issues. It is imminent to do the image restoration, image recognition to these image. This paper focuses on the equidistant discretization algorithm, in image pretreatment, and in image feature extraction study, focuses on image feature extraction algorithms based on attribute importance,c...

BACKGROUND AND PURPOSE Improved image quality is clinically desired for contrast-enhanced CT of the neck. We compared 30% adaptive statistical iterative reconstruction and model-based iterative reconstruction algorithms for the assessment of image quality of contrast-enhanced CT of the neck. MATERIALS AND METHODS Neck contrast-enhanced CT data from 64 consecutive patients were reconstructed r...

Document decomposition is a basic but crucial step for many document related applications. This paper proposes a novel approach to decompose document images into zones. It first generates overlapping zone hypotheses based on generic visual features. Then, each candidate zone is evaluated quantitatively by a learned generative zone model. We infer the optimal set of non-overlapping zones that co...

This paper proposes a new steganographic scheme relying on the principle of “cover-source switching”, the key idea being that the embedding should switch from one coversource to another. The proposed implementation, called Natural Steganography, considers the sensor noise naturally present in the raw images and uses the principle that, by the addition of a specific noise the steganographic embe...