Search results for "image processing"
showing 10 items of 3285 documents
“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…
Solutions to the 1-harmonic flow with values into a hyper-octant of the N-sphere
2013
Abstract We announce existence results for the 1-harmonic flow from a domain of R m into the first hyper-octant of the N -dimensional unit sphere, under homogeneous Neumann boundary conditions. The arguments rely on a notion of “geodesic representative” of a BV-vector field on its jump set.
THE 1-HARMONIC FLOW WITH VALUES IN A HYPEROCTANT OF THE N-SPHERE
2014
We prove the existence of solutions to the 1-harmonic flow — that is, the formal gradient flow of the total variation of a vector field with respect to the [math] -distance — from a domain of [math] into a hyperoctant of the [math] -dimensional unit sphere, [math] , under homogeneous Neumann boundary conditions. In particular, we characterize the lower-order term appearing in the Euler–Lagrange formulation in terms of the “geodesic representative” of a BV-director field on its jump set. Such characterization relies on a lower semicontinuity argument which leads to a nontrivial and nonconvex minimization problem: to find a shortest path between two points on [math] with respect to a metric w…
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…
Prediction of user action in moving-target selection tasks
2015
Selection of moving targets is a common, yet complex task in human–computer interaction (HCI), and more specifically in virtual reality (VR). Action prediction has proven to be the most comprehensive enhancement to address moving-target selection challenges. Current predictive techniques, however, heavily rely on continuous tracking of user actions, without considering the possibility that target-reaching actions may have a dominant pre-programmed component—this theory is known as the pre-programmed control theory.Thus, based on the pre-programmed control theory, this research explores the possibility of predicting moving-target selection prior to action execution. Specifically, three level…
WhoSNext: Recommending Twitter Users to Follow Using a Spreading Activation Network Based Approach
2020
The huge number of modern social network users has made the web a fertile ground for the growth and development of a plethora of recommender systems. To date, recommending a new user profile X to a given user U that could be interested in creating a relationship with X has been tackled using techniques based on content analysis, existing friendship relationships and other pieces of information coming from different social networks or websites. In this paper we propose a recommending architecture - called WhoSNext (WSN) - tested on Twitter and which aim is promoting the creation of new relationships among users. As recent researches show, this is an interesting recommendation problem: for a …
An intelligent architecture for service provisioning in pervasive environments
2011
Accepted version of an article from the conference: 2011 International Symposium on Innovations in Intelligent Systems and Applications (INISTA). Definitive published version available from IEEE: http://dx.doi.org/10.1109/INISTA.2011.5946134 The vision of pervasive environments is being realized more than ever with the proliferation of services and computing resources located in our surrounding environments. Identifying those services that deserve the attention of the user is becoming an increasingly-challenging task. In this paper, we present an adaptive multi-criteria decision making mechanism for recommending relevant services to the mobile user. In this context Relevance is determined b…
Image Processing and Measurement of the Bubble Properties in a Bubbling Fluidized Bed Reactor
2022
The efficiency of a fluidized bed reactor depends on the bed fluid dynamic behavior, which is significantly influenced by the bubble properties. This work investigates the bubble properties of a bubbling fluidized bed reactor using computational particle fluid dynamic (CPFD) simulations and electrical capacitance tomography (ECT) measurements. The two-dimensional images (along the reactor horizontal and vertical planes) of the fluidized bed are obtained from the CPFD simulations at different operating conditions. The CPFD model was developed in a commercial CPFD software Barracuda Virtual Reactor 20.0.1. The bubble behavior and bed fluidization behavior are characterized form the bubble pro…
Evaluating the impact of roughness in soil moisture and optical thickness retrievals over the VAS area
2014
International audience