Search results for "Segmentation"

Algorithmic Complexity Vulnerability Analysis of a Stateful Firewall

2016

Algorithmic complexity vulnerabilities are an opportunity for an ad-versary to conduct a sophisticated kind of attack i.e. on network infrastructure services. Such attacks take advantage of worst case time or space complexity of algorithms implemented on devices in their software. In this paper we address potential risks introduced by such algorithmic behavior in computer networks in particular on a stateful firewall. First we introduce the idea and theoretical background for the attack. We then describe in full detail a successfully con-ducted attack which takes advantage of the worst case computational complexi-ty of O(n2) of a hash table data structure used to store active sessions. The …

Rural tourism in Spain

2002

Abstract The aim of this study is to determine the features that characterize a new tourist class, called modern rural tourism, and to figure out the proportion of this market in one specific Spanish region. The geographical territory under study is El Alto Palancia, one of the best known rural resorts, within the Valencian region. In order to fulfil these goals, an empirical study was undertaken and an econometric model was applied afterwards. A wide set of variables has been selected for the Logit Binomial Model, which is shown to be useful in discriminating the modern from traditional tourists.

IMAGE PROCESSING, SEGMENTATION AND MACHINE LEARNING MODELS TO CLASSIFY AND DELINEATE TUMOR VOLUMES TO SUPPORT MEDICAL DECISION

2020

Techniques for processing and analysing images and medical data have become the main’s translational applications and researches in clinical and pre-clinical environments. The advantages of these techniques are the improvement of diagnosis accuracy and the assessment of treatment response by means of quantitative biomarkers in an efficient way. In the era of the personalized medicine, an early and efficacy prediction of therapy response in patients is still a critical issue. In radiation therapy planning, Magnetic Resonance Imaging (MRI) provides high quality detailed images and excellent soft-tissue contrast, while Computerized Tomography (CT) images provides attenuation maps and very good…

Extraction of Airways from CT (EXACT'09)

2012

Contains fulltext : 107854.pdf (Publisher’s version ) (Open Access) This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part o…

A gray-level 2D feature detector using circular statistics

1997

Abstract This paper presents a new method for corner and circular feature detection in gray-level images. It is based on the application of standard statistical techniques to the distribution of gradient orientations in a circular neighborhood of the prospective feature point. An evaluation using standard procedures and a comparison with other approaches is presented. Results show the robustness of this method as compared to the other corner detectors analyzed. The main novelties are the possibility of detecting points that are centers of circular symmetries, and discriminating between junctions, which are classified into corners (two-edge junctions) and multiple edge junctions.

UCS: Ultimate course search

2016

International audience; In this system prototype demonstration we present, Ultimate Course Search (UCS), a learning tool developed to provide students ways to efficiently search electronic educational materials. UCS integrates slides, lecture videos and textbooks into a single platform. The keywords extracted from the textbooks and the slides are the basis of the indexing scheme. For the videos, UCS relies on slide transitions and metadata to establish the correspondence between slides and video segments. The video segmentation is based on the slides being presented using the meta-data provided by the video recording software and image processing techniques.

Indexing Multimedia Learning Materials in Ultimate Course Search

2016

International audience; Multimedia is the main support for online learning materials and the size of multimedia learning materials is growing with the popularity of online programs offered by Universities. Ultimate Course Search (UCS) is a tool that aims to provide efficient search of course materials. UCS integrates slides, lecture videos and textbook content into a single platform with search capabilities. The keywords extracted from the textbook index and the power-point slides are the basis of the indexing scheme. The slides are indexed on the keywords and the videos are indexed on the slides. The correspondence between the slides and video segments is established using the meta-data pr…

Automatic Segmentation Using a Hybrid Dense Network Integrated With an 3D-Atrous Spatial Pyramid Pooling Module for Computed Tomography (CT) Imaging

2020

Computed tomography (CT) with a contrast-enhanced imaging technique is extensively proposed for the assessment and segmentation of multiple organs, especially organs at risk. It is an important factor involved in the decision making in clinical applications. Automatic segmentation and extraction of abdominal organs, such as thoracic organs at risk, from CT images are challenging tasks due to the low contrast of pixel values surrounding other organs. Various deep learning models based on 2D and 3D convolutional neural networks have been proposed for the segmentation of medical images because of their automatic feature extraction capability based on large labeled datasets. In this paper, we p…

A graph-based method for biological target volume segmentation

2013

The Usage of Quadtree in Deep Neural Networks to Represent Data For Navigation From a Monocular Camera

2022

Depth acquisition represents a key element for navigation tasks. It is, therefore, one of the major research topics in computer vision. Many approaches have been developed to address this problem by constructing the depth from series of images. However, there is a minimal case proposing a prediction from a single image, made possible with the emergence of deep learning approaches. The latter makes it possible to consider a reduction in both hardware and computing time costs, which is beneficial for embedded systems. However, network architecture remains a heavy process requiring a lot of GPU memory. Few approaches have proposed addressing this problem by developing lightweight architectures…