Search results for " Mach"
showing 10 items of 1388 documents
Deep Convolutional Neural Network for HEp-2 fluorescence intensity classification
2019
Indirect ImmunoFluorescence (IIF) assays are recommended as the gold standard method for detection of antinuclear antibodies (ANAs), which are of considerable importance in the diagnosis of autoimmune diseases. Fluorescence intensity analysis is very often complex, and depending on the capabilities of the operator, the association with incorrect classes is statistically easy. In this paper, we present a Convolutional Neural Network (CNN) system to classify positive/negative fluorescence intensity of HEp-2 IIF images, which is important for autoimmune diseases diagnosis. The method uses the best known pre-trained CNNs to extract features and a support vector machine (SVM) classifier for the …
A multi-process system for HEp-2 cells classification based on SVM
2016
An automatic system for pre-segmented IIF images analysis was developed.A non-standard pipeline for supervised image classification was adopted.The system uses a two-level pyramid to retain some spatial information.From each cell image 216 features are extracted.15 SVM classifiers one-against-one have been implemented. This study addresses the classification problem of the HEp-2 cells using indirect immunofluorescence (IIF) image analysis, which can indicate the presence of autoimmune diseases by finding antibodies in the patient serum. Recently, studies have shown that it is possible to identify the cell patterns using IIF image analysis and machine learning techniques. In this paper we de…
Automated detection of microaneurysms using robust blob descriptors
2013
International audience; Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fun…
An Automatic HEp-2 Specimen Analysis System Based on an Active Contours Model and an SVM Classification
2019
The antinuclear antibody (ANA) test is widely used for screening, diagnosing, and monitoring of autoimmune diseases. The most common methods to determine ANA are indirect immunofluorescence (IIF), performed by human epithelial type 2 (HEp-2) cells, as substrate antigen. The evaluation of ANA consist an analysis of fluorescence intensity and staining patterns. This paper presents a complete and fully automatic system able to characterize IIF images. The fluorescence intensity classification was obtained by performing an image preprocessing phase and implementing a Support Vector Machines (SVM) classifier. The cells identification problem has been addressed by developing a flexible segmentati…
What is the Natural Abstraction Level of an Algorithm?
2021
Abstract State Machines work with algorithms on the natural abstraction level. In this paper, we discuss the notion of the natural abstraction level of an algorithm and how ASM manage to capture this abstraction level. We will look into three areas of algorithms: the algorithm execution, the algorithm description, and the algorithm semantics. We conclude that ASM capture the natural abstraction level of the algorithm execution, but not necessarily of the algorithm description. ASM do also capture the natural abstraction level of execution semantics.
Distributed Computing on Distributed Memory
2018
Distributed computation is formalized in several description languages for computation, as e.g. Unified Modeling Language (UML), Specification and Description Language (SDL), and Concurrent Abstract State Machines (CASM). All these languages focus on the distribution of computation, which is somewhat the same as concurrent computation. In addition, there is also the aspect of distribution of state, which is often neglected. Distribution of state is most commonly represented by communication between active agents. This paper argues that it is desirable to abstract from the communication and to consider abstract distributed state. This includes semantic handling of conflict resolution, e.g. i…
Grammars++ for modelling information in text
1999
Abstract Grammars provide a convenient means to describe the set of valid instances in a text database. Flexibility in choosing a grammar can be exploited to provide information modelling capability by designing productions in the grammar to represent entities and relationships of interest to database applications. Additional constraints can be specified by attaching predicates to selected nonterminals in the grammar. When used for database definition, grammars can provide the functionality that users have come to expect of database schemas. Extended grammars can also be used to specify database manipulation, including query, update, view definition, and index specification.
A Comparison Study of Metaheuristic Techniques for Providing QoS to Avatars in DVE Systems
2004
Network-server architecture has become a de-facto standard for Distributed Virtual Environment (DVE) systems. In these systems, a large set of remote users share a 3D virtual scene. In order to design scalable DVE systems, different approaches have been proposed to maintain the DVE system working under its saturation point, maximizing system throughput. Also, in order to provide quality of service to avatars in a DVE systems, avatars should be assigned to servers taking into account, among other factors, system throughput and system latency. This highly complex problem is called quality of service (QoS) problem in DVE systems. This paper proposes two different approaches for solving the QoS…
Proactive Handoff of Secondary User in Cognitive Radio Network Using Machine Learning Techniques
2021
Spectrum management always appears as an essential part of modern communication systems. Handoff is initiated when the signal strength of a current user deteriorates below a certain threshold. In cognitive radio network, the perception of handoff is different due to the presence of two categories of users: certified/primary user and uncertified/secondary user. The reason for the spectrum handoff arises when the primary user (PU) returns to one of its band used by the secondary user. The spectrum handoff is of two types: reactive handoff and proactive handoff. There are certain limitations in reactive handoff, such as it suffers from prolonged handoff latency and interference. In the proacti…
Localization and Activity Classification of Unmanned Aerial Vehicle Using mmWave FMCW Radars
2021
In this article, we present a novel localization and activity classification method for aerial vehicle using mmWave frequency modulated continuous wave (FMCW) Radar. The localization and activity classification for aerial vehicle enables the utilization of mmWave Radars in security surveillance and privacy monitoring applications. In the proposed method, Radar’s antennas are oriented vertically to measure the elevation angle of arrival of the aerial vehicle from ground station. The height of the aerial vehicle and horizontal distance of the aerial vehicle from Radar station on ground are estimated using the measured radial range and the elevation angle of arrival. The aerial vehicle’s activ…