Search results for " Segmentation"
showing 10 items of 462 documents
MRI resolution enhancement using total variation regularization
2009
We propose a novel method for resolution enhancement for volumetric images based on a variational-based reconstruction approach. The reconstruction problem is posed using a deconvolution model that seeks to minimize the total variation norm of the image. Additionally, we propose a new edge-preserving operator that emphasizes and even enhances edges during the up-sampling and decimation of the image. The edge enhanced reconstruction is shown to yield significant improvement in resolution, especially preserving important edges containing anatomical information. This method is demonstrated as an enhancement tool for low-resolution, anisotropic, 3D brain MRI images, as well as a pre-processing …
Semantic Analysis of the Driving Environment in Urban Scenarios
2021
Understanding urban scenes require recognizing the semantic constituents of a scene and the complex interactions between them. In this work, we explore and provide effective representations for understanding urban scenes based on in situ perception, which can be helpful for planning and decision-making in various complex urban environments and under a variety of environmental conditions. We first present a taxonomy of deep learning methods in the area of semantic segmentation, the most studied topic in the literature for understanding urban driving scenes. The methods are categorized based on their architectural structure and further elaborated with a discussion of their advantages, possibl…
Marketing Sri Lanka as an International Tourist Destination
2007
Masteroppgave i økonomi og administrasjon 2007 - Høgskolen i Agder, Kristiansand Within the last two decades Sri Lanka’s tourism industry has grown dramatically as one of the main foreign exchange earners and employment provider. Since Sri Lanka depends enormously on tourism for its growth and development, this paper provides an analysis of marketing efforts within the tourism industry in Sri Lanka for foreign tourists. In compliance with this trend, the purpose of this thesis and research is to review Sri Lanka as an international tourist destination and its current marketing activities in the tourism trade, to investigate the proper use of marketing efforts, and to suggest guidelines for …
Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging.
2007
A new fast and accurate tissue typing technique has recently been successfully applied to prostate MR spectroscopic imaging (MRSI) data. This technique is based on canonical correlation analysis (CCA), a statistical method able to simultaneously exploit the spectral and spatial information characterizing the MRSI data. Here, the performance of CCA is further investigated by using brain data obtained by two-dimensional turbo spectroscopic imaging (2DTSI) from patients affected by glioblastoma. The purpose of this study is to investigate the applicability of CCA when typing tissues of heterogeneous tumors. The performance of CCA is also compared with that of ordinary correlation analysis on s…
Hidden Markov random field model and Broyden–Fletcher–Goldfarb–Shanno algorithm for brain image segmentation
2018
International audience; Many routine medical examinations produce images of patients suffering from various pathologies. With the huge number of medical images, the manual analysis and interpretation became a tedious task. Thus, automatic image segmentation became essential for diagnosis assistance. Segmentation consists in dividing the image into homogeneous and significant regions. We focus on hidden Markov random fields referred to as HMRF to model the problem of segmentation. This modelisation leads to a classical function minimisation problem. Broyden-Fletcher-Goldfarb-Shanno algorithm referred to as BFGS is one of the most powerful methods to solve unconstrained optimisation problem. …
Depth Map Generation by Image Classification
2004
This paper presents a novel and fully automatic technique to estimate depth information from a single input image. The proposed method is based on a new image classification technique able to classify digital images (also in Bayer pattern format) as indoor, outdoor with geometric elements or outdoor without geometric elements. Using the information collected in the classification step a suitable depth map is estimated. The proposed technique is fully unsupervised and is able to generate depth map from a single view of the scene, requiring low computational resources.
Using discourse segmentation to account for the polyfunctionality of discourse markers:The case of well
2021
Abstract A large number of studies describe the many different functions of polyfunctional discourse markers like well in different contexts and from different theoretical perspectives. In the current paper, we propose to systematize the many different uses identified based on their position with respect to the discourse units they are associated with. Not only can previous findings on well be integrated into a single coherent representation of its uses and functions, but the positions with respect to the discourse units can also be associated with specific functions, thus shedding light on how the polyfunctionality of well is brought about.
Discrete wavelet transform based multispectral filter array demosaicking
2013
International audience; The idea of colour filter array may be adapted to multi-spectral image acquisition by integrating more filter types into the array, and developing associated demosaicking algorithms. Several methods employing discrete wavelet transform (DWT) have been proposed for CFA demosaicking. In this work, we put forward an extended use of DWT for mul-tispectral filter array demosaicking. The extension seemed straightforward, however we observed striking results. This work contributes to better understanding of the issue by demonstrating that spectral correlation and spatial resolution of the images exerts a crucial influence on the performance of DWT based demosaicking.
Attuned HRM Systems for Social Enterprises
2021
This paper is motivated by a puzzling observation made when conducting a case study of ProCredit (PC), a well-known social bank. The HR practices that this social enterprise (SE) adopted to cultivate mission identification were unfavorably impacting its retention rate. Building on prior research and our analysis of the case, we argue the need for SEs to embrace HRM systems that are both mission-identification proactive and employee-retention preemptive. It theorizes that these HRM systems should be attuned to the labor market conditions (e.g., market segmentation and competition for employees) that frame how SEs develop and sustain Person-Organization (P-O) fit. Attuned HRM systems are adap…
Determinantes del comportamiento de queja y su importancia en la segmentación de clientes insatisfechos
2008
ResumenEsta investigación de carácter exploratorio aborda el proceso de formación del comportamiento de queja utilizando el proceso de segmentación de clientes. Consideramos que dicho comportamiento agrupa dos tipos de respuestas a la insatisfacción: las respuestas de queja y las respuestas privadas. Nuestro objetivo es conocer la capacidad que tiene la intensidad de la insatisfacción y otras variables relevantes de la literatura en la discriminación de segmentos de consumidores, con el propósito de estudiar sus comportamientos y características. La metodología de análisis CHAID ha permitido segmentar la muestra en diferentes grupos identificando los principales antecedentes de ambos tipos …