This paper develops a general, formal framework for modeling term dependencies via Markov random fields. The model allows for arbitrary text features to be incorporated as evidence. In particular, we make use of features based on occurrences of single terms, ordered phrases, and unordered phrases. We explore full independence, sequential dependence, and full dependence variants of the model. A ...

This theoretical paper is concerned with the structure learning limit for Gaussian Markov random fields from i.i.d. samples. The common strategy is applying the Fano method to a family of restricted ensembles. The efficiency of this method, however, depends crucially on selected restricted ensembles. To break through this limitation, we analyze the whole graph ensemble from a group theoretical ...

This paper presents a novel method of foreground and shadow segmentation in monocular indoor image sequences. The models of background, edge information, and shadow are set up and adaptively updated. A Bayesian network is proposed to describe the relationships among the segmentation label, background, intensity, and edge information. A maximum a posteriori—Markov random field estimation is used...

Using robots in precision farming has the potential to reduce the reliance on herbicides and pesticides through selectively spraying individual plants or through manual weed removal. A prerequisite for that is the ability of the robot to separate and identify the value crops and the weeds on the field. Based on the output of the robot’s perception system, it can trigger the actuators for sprayi...

In this paper, we present a new automatic segmentation method for magnetic resonance images. The aim of this segmentation is to divide the brain into homogeneous regions and to detect the presence of tumors. Our method is divided into two parts. First, we make a pre-segmentation to extract the brain from the head. Then, a second segmentation is done inside the brain. Several techniques are comb...

Several segmentation techniques were evaluated for their effectiveness in distinguishing lesion from background in dermatoscopic images of pigmented lesions (moles and melanomas). These included 5 techniques previously used for segmentation of pigmented lesions, and several new techniques based on stabilized inverse diffusion equations (SIDE) and Markov random fields (MRF). Novel multiresolutio...

In this study we explore a novel technique for creation of polarity lexicons from the Twitter streams in Russian and English. With this aim we make preliminary filtering of subjective tweets using general domain-independent lexicons in each language. Then the subjective tweets are used for extraction of domain-specific sentiment words. Relying on co-occurrence statistics of extracted words in a...

Kurzfassung. In diesem Beitrag wird eine neuartige Methode für die nichtlineare Bildregistrierung vorgestellt. Dabei wird das klassische Energieminimierungsproblem Intensitäts-basierter Methoden in eine Markov Random Field Formulierung eingebettet. Dieses ermöglicht die Nutzung von effizienten diskreten Optimierungsmethoden, die unabhängig von der tatsächlich verwendeten Kostenfunktion eine qua...

The thermodynamics of the Bose–Fermi–Hubbard model with direct interaction between neighbour bosonic particles is considered in this work at finite temperature. The hard-core boson case is considered and the pseudospin formalism is used. Charge susceptibility of the system is calculated and the possibilities of the transitions to the charge density wave order, superfluid and supersolid phases a...

The classification of 3d point cloud data is an important component of applications such as map generation and architectural modeling. However, the complexity of the scenes together with the level of noise in the data acquired through mobile laser range-scanning make this task quite difficult. We propose a novel classification method that relies on a combination of edge, node, and relative dens...