Search results for " Classification"

Normal and Abnormal Tissue Classification in Positron Emission Tomography Oncological Studies

2018

Positron Emission Tomography (PET) imaging is increasingly used in radiotherapy environment as well as for staging and assessing treatment response. The ability to classify PET tissues, as normal versus abnormal tissues, is crucial for medical analysis and interpretation. For this reason, a system for classifying PET area is implemented and validated. The proposed classification is carried out using k-nearest neighbor (KNN) method with the stratified K-Fold Cross-Validation strategy to enhance the classifier reliability. A dataset of eighty oncological patients are collected for system training and validation. For every patient, lesion (abnormal tissue) and background (normal tissue around …

Evaluating objective measures of impairment to trunk strength and control for cross-country sit skiing

2021

AbstractIn Paralympic cross-country sit skiing, athlete classification is performed by an expert panel, so it may be affected by subjectivity. An evidence-based classification is required, in which objective measures of impairment must be identified. The purposes of this study were: (i) to evaluate the reliability of 5 trunk strength measures and 18 trunk control measures developed for the purposes of classification; (ii) to rank the objective measures, according to the largest effects on performance. Using a new testing device, 14 elite sit-skiers performed two upright seated press tests and one simulated poling test to evaluate trunk strength. They were also subjected to unpredictable bal…

Gianfrancesco Maineri, Paolo da San Leocadio i la gènesi d?un model de Crist portacreu

2020

[CA] El present article es centra en la vinculació entre els diversos exemplars de Crist portacreu de Gianfrancesco Maineri i els homònims de Paolo da San Leocadio. A través de diverses comparacions, tractarà d¿explicar-se la gènesi d¿aquest model, aportant, a més, dades que permetran una millor classificació dels exemplars leocadians. Finalment, es realitzen una sèrie de reflexions entorn de l¿hipotètic retorn de San Leocadio a Itàlia (1485-1489) i a la seua possible vinculació amb Maineri.

Gauss words and the topology of finitely determined map germs from R^n to R^n

2013

El objetivo de este trabajo es la clasificación topológica de gérmenes de aplicación finitamente determinados en el caso real equidimensional, es decir, de R^n en R^n, mediante la construcción de un invariante topológico completo asociado al link de dichos gérmenes. El link se define como la intersección de la imagen de un representante de nuestro germen f con una esfera S^n centrada en el origen y suficientemente pequeña. Para el caso n=2, una vez construido dicho invariante (las palabras de Gauss adaptadas a este caso particular), obtenemos la clasificación topológica de dichos gérmenes prácticamente en su totalidad en el caso de corrango 1 y parcialmente en el caso de corrango 2. Por últ…

European evidence-based recommendations for clinical assessment of upper limb in neurorehabilitation (CAULIN): data synthesis from systematic reviews…

2021

Abstract Background Technology-supported rehabilitation can help alleviate the increasing need for cost-effective rehabilitation of neurological conditions, but use in clinical practice remains limited. Agreement on a core set of reliable, valid and accessible outcome measures to assess rehabilitation outcomes is needed to generate strong evidence about effectiveness of rehabilitation approaches, including technologies. This paper collates and synthesizes a core set from multiple sources; combining existing evidence, clinical practice guidelines and expert consensus into European recommendations for Clinical Assessment of Upper Limb In Neurorehabilitation (CAULIN). Methods Data from systema…

“Anti-Bayesian” parametric pattern classification using order statistics criteria for some members of the exponential family

2013

This paper submits a comprehensive report of the use of order statistics (OS) for parametric pattern recognition (PR) for various distributions within the exponential family. Although the field of parametric PR has been thoroughly studied for over five decades, the use of the OS of the distributions to achieve this has not been reported. The pioneering work on using OS for classification was presented earlier for the uniform distribution and for some members of the exponential family, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean. A…

Bot recognition in a Web store: An approach based on unsupervised learning

2020

Abstract Web traffic on e-business sites is increasingly dominated by artificial agents (Web bots) which pose a threat to the website security, privacy, and performance. To develop efficient bot detection methods and discover reliable e-customer behavioural patterns, the accurate separation of traffic generated by legitimate users and Web bots is necessary. This paper proposes a machine learning solution to the problem of bot and human session classification, with a specific application to e-commerce. The approach studied in this work explores the use of unsupervised learning (k-means and Graded Possibilistic c-Means), followed by supervised labelling of clusters, a generative learning stra…

Classification par méthodes d’apprentissage supervisé et faiblement superviséd’images multimodales pour l’aide au diagnostic du lentigo malin en derm…

2021

Carried out in collaboration with the Saint-Étienne University Hospital, this work provides additional information to help the skin diagnosis by providing new decision methods on Lentigo Maligna and Lentigo Maligna Melanoma pathologies. To this end, the modalities regularly used in clinical conditions are made available to this work and are orchestrated within a multimodal process. Among image modalities, may be mentioned the clinical photography, the dermatoscopy, and the confocal reflectance microscopy. Initially, the first steps of this manuscript focus on reflectance confocal microscopy as the work in computer diagnostic assistance is relatively underdeveloped, in particular on the dete…

2021

In COVID-19 related infodemic, social media becomes a medium for wrongdoers to spread rumors, fake news, hoaxes, conspiracies, astroturf memes, clickbait, satire, smear campaigns, and other forms of deception. It puts a tremendous strain on society by damaging reputation, public trust, freedom of expression, journalism, justice, truth, and democracy. Therefore, it is of paramount importance to detect and contain unreliable information. Multiple techniques have been proposed to detect fake news propagation in tweets based on tweets content, propagation on the network of users, and the profile of the news generators. Generating human-like content allows deceiving content-based methods. Networ…

Anomaly Detection in Traffic Surveillance Videos Using Deep Learning

2022

In the recent past, a huge number of cameras have been placed in a variety of public and private areas for the purposes of surveillance, the monitoring of abnormal human actions, and traffic surveillance. The detection and recognition of abnormal activity in a real-world environment is a big challenge, as there can be many types of alarming and abnormal activities, such as theft, violence, and accidents. This research deals with accidents in traffic videos. In the modern world, video traffic surveillance cameras (VTSS) are used for traffic surveillance and monitoring. As the population is increasing drastically, the likelihood of accidents is also increasing. The VTSS is used to detect abno…