Search results for "VISION"
showing 10 items of 5066 documents
Anchoring symbols to conceptual spaces: the case of dynamic scenarios.
2003
In recent years, there have been several proposals for the realization of models inspired to biological solutions for pattern recognition. In this work we propose a new approach, based on a hierarchical modular structure, to realize a system capable to learn by examples and recognize objects in digital images. The adopted techniques are based on multiresolution image analysis and neural networks. Performance on two different data sets and experimental timings on a single instruction multiple data (SIMD) machine are also reported.
Conceptual spaces for computer vision representations
2001
A framework for high-level representations in computer vision architectures is described. The framework is based on the notion of conceptual space. This approach allows us to define a conceptual semantics for the symbolic representations of the vision system. In this way, the semantics of the symbols can be grounded to the data coming from the sensors. In addition, the proposed approach generalizes the most popular frameworks adopted in computer vision.
Arabic Named Entity Recognition: A Feature-Driven Study
2009
The named entity recognition task aims at identifying and classifying named entities within an open-domain text. This task has been garnering significant attention recently as it has been shown to help improve the performance of many natural language processing applications. In this paper, we investigate the impact of using different sets of features in three discriminative machine learning frameworks, namely, support vector machines, maximum entropy and conditional random fields for the task of named entity recognition. Our language of interest is Arabic. We explore lexical, contextual and morphological features and nine data-sets of different genres and annotations. We measure the impact …
On general conditional prevision assessments
2009
In this paper we consider general conditional random quantities of the kind $X|Y$, where $X$ and $Y$ are finite discrete random quantities. Then, we introduce the notion of coherence for conditional prevision assessments on finite families of general conditional random quantities. Moreover, we give a compound prevision theorem and we examine the relation between the previsions of $X|Y$ and $Y|X$. Then, we give some results on random gains and, by a suitable alternative theorem, we obtain a characterization of coherence. We also propose an algorithm for the checking of coherence. Finally, we briefly examine the case of imprecise conditional prevision assessments by introducing the notions of…
Partecipazione digitale: strumenti, scenari, potenzialità
2013
La costruzione dell’immagine collettiva dello spazio è alla base del senso di appartenenza e di identità che costituisce una parte essenziale della cultura urbana. Esso è fondamentale per lo sviluppo di un’adeguata coscienza civica e per l’attivazione di processi partecipativi effettivamente validi ed efficaci. La diffusione delle nuove tecnologie informatiche, accessibili anche ad utenti non specializzati, apre una serie molteplice di scenari in cui lo scambio e la condivisione, nonché la co-produzione dell’informazione georeferenziata, costituiscono un’opportunità di interazione tra abitanti di un territorio e decisori politici ed istituzionali. Certamente lo studio sistematico di iniziat…
The SISCone jet algorithm optimised for low particle multiplicities
2011
The SISCone jet algorithm is a seedless infrared-safe cone jet algorithm. There exists an implementation which is highly optimised for a large number of final state particles. However, in fixed-order perturbative calculations with a small number of final state particles, it turns out that the computer time needed for the jet clustering of this implementation is comparable to the computer time of the matrix elements. This article reports on an implementation of the SISCone algorithm optimised for low particle multiplicities.
Automated detection of patient movement during a CBCT scan based on the projection data.
2015
Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evalu…
Metal artifact reduction in x-ray computed tomography: Inpainting versus missing value
2011
A comparison of algorithms for reduction of metal artifacts in x-ray cone beam computed tomography (CBCT) is presented. In the context of algebraic reconstruction techniques (ART) several inpainting algorithms in the image domain are evaluated against missing data strategies. A GPU-based iterative framework is employed for a meaningful comparison of both. Simulation results from an extended Shepp-Logan phantom and real world dental data are given.
Alignment of cone beam computed tomography data using intra-oral fiducial markers.
2009
This article illustrates a new method to align and merge two partially overlapping volumes each of them generated by cone beam computed tomography (CBCT). The aggregate volume covers a larger area of investigation and is determined by localizing one fixed LEGO brick in both of the primal volumes. Based on the LEGO brick an approximate registration of the volumes is determined. Afterwards we improve the transformation by minimizing the difference in overlapping space. In this paper we present a method which automates these two steps and provides an aligned volume.
Motion Artifact Detection in Confocal Laser Endomicroscopy Images
2018
Confocal Laser Endomicroscopy (CLE), an optical imaging technique allowing non-invasive examination of the mucosa on a (sub)- cellular level, has proven to be a valuable diagnostic tool in gastroenterology and shows promising results in various anatomical regions including the oral cavity. Recently, the feasibility of automatic carcinoma detection for CLE images of sufficient quality was shown. However, in real world data sets a high amount of CLE images is corrupted by artifacts. Amongst the most prevalent artifact types are motion-induced image deteriorations. In the scope of this work, algorithmic approaches for the automatic detection of motion artifact-tainted image regions were develo…