Search results for "Pattern recognition"
showing 10 items of 2301 documents
Computer-assisted clinical diagnosis in the official European union languages
2016
eHealth services integrate Web Information Retrieval and Intelligent Medical Decision Support for health care professionals based on the range of possible symptoms which a patient reports. However, many symptoms like high temperature, fever, or headache, are ambiguous in terms of suggesting wide variety of possible patient's conditions to the GP, while other symptoms are mutually dependant, which again can be misleading to make an accurate diagnosis. On the other hand, doctor's up-to-date knowledge on the medicaments, drugs, active medical substances included, anticipated range of diseases relating to the symptoms reported, and the most reliable pharmaceutical manufacturers, are of the grea…
An automated image analysis methodology for classifying megakaryocytes in chronic myeloproliferative disorders
2008
This work describes an automatic method for discrimination in microphotographs between normal and pathological human megakaryocytes and between two kinds of disorders of these cells. A segmentation procedure has been developed, mainly based on mathematical morphology and wavelet transform, to isolate the cells. The features of each megakaryocyte (e.g. area, perimeter and tortuosity of the cell and its nucleus, and shape complexity via elliptic Fourier transform) are used by a regression tree procedure applied twice: the first time to find the set of normal megakaryocytes and the second to distinguish between the pathologies. The output of our classifier has been compared to the interpretati…
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…
Compréhension de scènes urbaines basées sur la polarisation
2021
Humans possess an innate ability to interpret scenes under any condition. Computer Vision tends to mimic these capabilities by implementing intelligent algorithms to address complex understanding problems. In this regard, we are interested in understanding outdoor urban scenes in various weather conditions. This thesis specifically addresses the problems arising from the presence of specularity in the scenes. To this end, we aim to take advantage of polarization indices to define such surfaces in addition to traditional objects. In terms of understanding, we aim to introduce polarization to the fields of computer vision and deep learning.This thesis focuses on the following underlying challeng…
Feature selection for KNN classifier to improve accurate detection of subthalamic nucleus during deep brain stimulation surgery in Parkinson’s patien…
2017
The tremor and dystonia associated with Parkinson’s disease can be treated with deep brain stimulation (DBS) implanted into the subthalamic nucleus (STN). The accurate STN detection is a complex neurosurgeon task during a DBS surgery since a proper fixing of stimulating electrodes will impact on the patient’s future life. The brain electrical signals obtained with Micro Electrodes Register (MER) are acquired at different depths of the brain during DBS surgery to detect STN. In our previous work, we found good accuracy performance to improve the localization of STN using K-Nearest Neighbours (KNN) supervised learning algorithm. However, for real-time classification, it is essential to reduce…
Composite Scaffolds with a Hydrohyapatite Spatial Gradient for Osteochondral Defect Repair
2018
Osteochondral defects derived by traumatic injury or aging related disease are often associated with severe joint pain and progressive loss of joint functions for millions of people worldwide and represent a major challenge for the orthopedic community. Tissue engineering offers new therapeutic approach to repair the osteochondral defects, through the production of scaffolds manufactured to mimic their complex architecture, which consists of cartilage and bone layers. Composite scaffolds based on a PLLA polymeric matrix containing hydroxyapatite (HA) as a filler were prepared through a modified thermally induced phase separation (TIPS) protocol. A suspension was prepared by adding sieved HA…
Nonlinear rotation-invariant pattern recognition by use of the optical morphological correlation.
2000
We introduce a modification of the nonlinear morphological correlation for optical rotation-invariant pattern recognition. The high selectivity of the morphological correlation is conserved compared with standard linear correlation. The operation performs the common morphological correlation by extraction of the information by means of a circular-harmonic component of a reference. In spite of some loss of information good discrimination is obtained, especially for detecting images with a high degree of resemblance. Computer simulations are presented, as well as optical experiments implemented with a joint transform correlator.
Eulerian-Eulerian modelling and computational fluid dynamics simulation of wire mesh demisters in MSF plants
2014
Purpose – The purpose of this study is to focus on simulation of wire mesh demisters in multistage flash desalination (MSF) plants. The simulation is made by the use of computational fluid dynamics (CFD) software. Design/methodology/approach – A steady state and two-dimensional (2D) model was developed to simulate the demister. The model employs an Eulerian-Eulerian approach to simulate the flow of water vapor and brine droplets in the demister. The computational domain included three zones, which are the vapor space above and below the demister and the demister. The demister zone was modeled as a tube bank arrange or as a porous media. Findings – Sensitivity analysis of the model showed t…
Denoising 3D Models with Attributes using Soft Thresholding
2004
International audience; Recent advances in scanning and acquisition technologies allow the construction of complex models from real world scenes. However, the data of those models are generally corrupted by measurement errors. This paper describes an efficient single pass algorithm for denoising irregular meshes of scanned 3D model surfaces. In this algorithm, the frequency content of the model is assessed by a multiresolution analysis that requires only 1-ring neighbourhood without any particular parameterization of the model faces. Denoising is achieved by applying the soft thresholding method to the detail coefficients given by the multiresolution analysis. Our method is suitable for irr…
Space-Time FPCA Clustering of Multidimensional Curves.
2018
In this paper we focus on finding clusters of multidimensional curves with spatio-temporal structure, applying a variant of a k-means algorithm based on the principal component rotation of data. The main advantage of this approach is to combine the clustering functional analysis of the multidimensional data, with smoothing methods based on generalized additive models, that cope with both the spatial and the temporal variability, and with functional principal components that takes into account the dependency between the curves.