Search results for "Image processing"
showing 10 items of 3285 documents
Giving patients secure " google-like " access to their medical record
2008
International audience; The main problem for the patient who wants to have access to all of the information about his health is that this information is very often spread over many medical records. Therefore, it would be convenient for the patient, after being identified and authenticated, to use a kind of specific medical search engine as one part of the solution to this main problem. The principal objective is for the patient to have access to his or her medical information at anytime and wherever it has been stored. This proposal for secure "Google Like" access requires the addition of different conditions: very strict identity checks using cryptographic techniques such as those planned …
Iterative Learning Applied to Hydraulic Pressure Control
2018
This paper addresses a performance limiting phenomenon that may occur in the pressure control of hydraulic actuators subjected to external velocity disturbances. It is demonstrated that under certain conditions a severe peaking of the control error may be observed that significantly degrades the performance of the system due to the presence of nonlinearities. The phenomenon is investigated numerically and experimentally using a system that requires pressure control of two hydraulic cylinders. It is demonstrated that the common solution of feed forwarding the velocity disturbance is not effective in reducing the peaking that occurs as a result of this phenomenon. To improve the system perfor…
Active lighting applied to three-dimensional reconstruction of specular metallic surfaces by polarization imaging
2006
International audience; In the field of industrial vision, the three-dimensional inspection of highly reflective metallic objects is still a delicate task. We deal with a new automated three-dimensional inspection system based on polarization analysis. We first present an extension of the shape-from-polarization method for dielectric surfaces to metallic surfaces. Then, we describe what we believe to be a new way of solving the ambiguity concerning the normal orientation with an active lighting system. Finally, applications to shape-defect detection are discussed, and the efficiency of the system to discriminate defects on specular metallic objects made by stamping and polishing is presente…
Interactively Learning the Preferences of a Decision Maker in Multi-objective Optimization Utilizing Belief-rules
2020
Many real life problems can be modelled as multiobjective optimization problems. Such problems often consist of multiple conflicting objectives to be optimized simultaneously. Multiple optimal solutions exist to these problems, and a single solution cannot be said to be the best without preferences given by a domain expert. Preferences can be used to find satisfying solutions: optimal solutions, which best match the expert’s preferences. To model the preferences of the expert, and aid him/her in finding satisfying solutions, a novel method is proposed. The method utilizes machine learning combined with belief-rule based systems to adaptively train a belief rule based system to learn a domai…
Employer brand management: methodological aspects
2021
У статті обгрунтовано необхідність залучення зовнішніх ресурсів для управління брендом роботодавця. У роботі авторами було схематизовано процес прийняття рішення щодо обгрунтованого вибору компаній аутсорсерів. При цьому сформовано систему критеріїв здійснення такого вибору, що включає як вимоги до компанії-аутсорсера, так і вимоги до майбутнього проекту: рівень вдалих попередніх проектів; рівень задоволеності клієнтів; досвід роботи в Україні; середня вартість послуг аутсорсингової компанії з розробки проекту; термін розробки проекту; комплексність розроблених рекомендацій щодо просування бренду роботодавця; термін дії проекту; гнучкість проекту; рівень складності впровадження проекту; сер…
Modal Consequence Relations Extending S4.3: An Application of Projective Unification
2016
We characterize all finitary consequence relations over $\mathbf{S4.3}$ , both syntactically, by exhibiting so-called (admissible) passive rules that extend the given logic, and semantically, by providing suitable strongly adequate classes of algebras. This is achieved by applying an earlier result stating that a modal logic $L$ extending $\mathbf{S4}$ has projective unification if and only if $L$ contains $\mathbf{S4.3}$ . In particular, we show that these consequence relations enjoy the strong finite model property, and are finitely based. In this way, we extend the known results by Bull and Fine, from logics, to consequence relations. We also show that the lattice of consequence relation…
Scheduling under the network of temporo-spatial proximity relationships
2017
We discuss and introduce to the schedulingeld a novel, qualitative optimization model - scheduling under the network of temporo-spatial proximity relationships.We introduce a half perimeter proximity measure as an objective of scheduling.We present and evaluate an incremental Sequence Pair neighborhood evaluation algorithm, applicable to both scheduling and rectangle packing problems in VLSI industry. In this paper, we discuss and introduce to the scheduling field a novel optimization objective - half perimeter proximity measure in scheduling under the network of temporo-spatial proximity relationships. The presented approach enables to qualitatively express various reasons of scheduling ce…
Causality-Aware Convolutional Neural Networks for Advanced Image Classification and Generation
2023
Smart manufacturing uses emerging deep learning models, and particularly Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs), for different industrial diagnostics tasks, e.g., classification, detection, recognition, prediction, synthetic data generation, security, etc., on the basis of image data. In spite of being efficient for these objectives, the majority of current deep learning models lack interpretability and explainability. They can discover features hidden within input data together with their mutual co-occurrence. However, they are weak at discovering and making explicit hidden causalities between the features, which could be the reason behind the parti…
A Stochastic Decision Process Model for Optimization of Railway and Tramway Track Maintenance by means of Image Processing Technique
2013
One of the key targets for an efficient transport network management is the search for proper maintenance policies to guarantee acceptable safety and quality standards in the travel and to optimize available resource allocation. Methodologically, the proposed model presented in this paper uses the stochastic dynamic programming and in particular Markov decision processes applied to the rail wear conditions for the railway and tramway network. By performing the integrated analysis of the classes of variables which characterize the rail quality (in terms of safety), the proposed mathematical approach allows to find the solutions to the decision-making process related to the probability of det…
Automated Railway Signs Detection. Preliminary Results
2019
Abstract Nowadays safety in railways is mostly achieved by automated system technologies such as ERTMS/ETCS. Nevertheless, on local railways (suburban and regional lines) several tasks still depend on the choices and actions of a human crew. With the aim to improve safety in such type of railways, this research proposes a system for the automatic detection and recognition of railway signs by means of the digital image processing technique. First field applications, carried out on the Italian railway network, show that the proposed system is very accurate (the percentage of correctly detected railway signs is about 97%), even at high train speeds.