A novel approach to obtain precise segmentation of synthetic aperture radar (SAR) images using Markov random field model on region adjacency graph (MRF-RAG) is presented. First, to form a RAG, the watershed algorithm is employed to obtain an initially over-segmented image. Then, a novel MRF is defined over the RAG instead of pixels so that the erroneous segmentation caused by speckle in SAR ima...

Herein, we propose a new Markov random field (MRF) image segmentation model which aims at combining color and texture features. The model has a multi-layer structure: Each feature has its own layer, called feature layer, where an MRF model is defined using only the corresponding feature. A special layer is assigned to the combined MRF model. This layer interacts with each feature layer and prov...

Multi-view range image integration aims at producing a single reasonable 3D point cloud. The point cloud is likely to be inconsistent with the measurements topologically and geometrically due to registration errors and scanning noise. This paper proposes a novel integration method cast in the framework of Markov random fields (MRF). We define a probabilistic description of a MRF model designed ...

In incremental databases, new transactions will add continuously to the old transactions. Maximal frequent patterns are one of the condensed representations of frequent patterns. Recently, regular pattern mining along with frequent patterns playing an important role in data mining research. Several algorithms have been proposed so far to mine maximal frequent patterns on various domains. There ...

The purpose of this work is to evaluate methods from deep learning for application to Magnetic Resonance Fingerprinting (MRF). MRF is a recently proposed measurement technique for generating quantitative parameter maps. In MRF a non-steady state signal is generated by a pseudo-random excitation pattern. A comparison of the measured signal in each voxel with the physical model yields quantitativ...

A new method for the automated extraction of pipelines and other linear objects from Synthetic Aperture Radar (SAR) scenes is presented. It combines intensity data with coherence data from an interferometric evaluation of a SAR scene pair. The fusion is based on Bayesian statistics and is part of a Markov random Ž eld (MRF) model for line extraction. Both intensity and coherence data are evalua...

In this paper we describe a design of an innovative immersive Haptic Black Box (HBB) based on Magneto Rheological Fluids (MRF). By exploiting results from an accurate analysis performed on a previously operating haptic display a new device capable of exciting the MRF with improved performance in terms of magnetic field intensity and spatial resolution has been developed. Due to the core structu...

We explore the application of concepts developed in High Energy Physics (HEP) for advanced medical data analysis. Our study case is a problem with high social impact: clinically-feasible Magnetic Resonance Fingerprinting (MRF). MRF new, quantitative, imaging technique that replaces multiple qualitative Imaging (MRI) exams single, reproducible measurement increased sensitivity and efficiency. A ...

This paper studies how to incorporate the external word correlation knowledge to improve the coherence of topic modeling. Existing topic models assume words are generated independently and lack the mechanism to utilize the rich similarity relationships among words to learn coherent topics. To solve this problem, we build a Markov Random Field (MRF) regularized Latent Dirichlet Allocation (LDA) ...

A number of clinical studies indicate the coexistence of multiple chronic pelvic diseases and pain syndromes. An association between various conditions related to the pelvic viscera may relate to a high degree of central visceral convergence, which is a requisite for the cross-organ coordination that is necessary for their normal functions. In the present study, a population of neurons receivin...