Working Paper

Face recognition and verification with deep neural networks

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
Clustering is probably the most used techniques in the analysis of gene expression data. The goal of this technique is to find clusters of genes that have similar expression patterns. The basic assumption behind clustering approaches is that two genes with similar expression patterns are mechanically related. There are many ways in which two genes could be related (when activated by the same transcription factor, when one acts as a transcription factor for the other, when involved in the same biological process and therefore similarly regulated by the cell, etc.). This work will refer to a previously presented research paper-Yeast Metabolic Cycle-which studies genes that have similar expression patterns, we will use them to demonstrate how data mining techniques are applied to bioinformatics. A variety of tools is leveraged in order to apply Clustering and Bi clustering techniques and gains a better understanding of the biological problems we encounter in the field of systems biology.
Article
Full-text available
There has been continuous research in the energy distribution sector because of its huge impact on modern societies. Nonetheless, aerial high voltage power lines are still supported by old transmission towers which involve some serious risks. Those risks may be avoided with periodic and expensive reviews. The main objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. More specifically, the work is focused on reducing the number of periodic reviews of transmission towers to avoid step and touch potentials, which are very dangerous for humans. A virtual organization-based multi-agent system is proposed in conjunction with different artificial intelligence methods and algorithms. The developed system is able to propose a sample of transmission towers from a selected set to be reviewed. The system ensures that the whole set will have similar values without needing to review all the transmission towers. As a result of this work, a website application is provided to manage all the review processes and all the transmission towers of Spain. It allows the companies that review the transmission towers to initiate a new review process for a whole line or area, while the system indicates the transmission towers to review. The system is also able to recommend the best place to locate a new transmission tower or the best type of structure to use when a new transmission tower must be used.
Conference Paper
Full-text available
Autonomous vehicles are becoming one of the developmental elements , not only for the transport of people but also in the field of data collection and monitoring, control of external elements or supervision and security. Their advantage is the ability to access dangerous areas which often cannot be accessed by humans. It is necessary that the vehicle recognizes its surrounding and reacts in an adequate way. In this work a study was carried out of the main techniques of artificial vision, machine learning and supervised learning applied in vehicles so they recognize the road and do not leave it. This work presents the viability of the different machine learning techniques for their application in the problem of autonomous driving. For this, an automobile robotic prototype has been constructed and an algorithm has been developed based on the Artificial Neural Network (ANN) algorithm and a user application which allows to carry out all integrated analysis and observe in real-time the vehicle's view and the processing of the different snapshots. We have also demonstrated that the application of the stated algorithm, diverse processing techniques and artificial vision was sufficient, so that our robot could drive with precision and keep on the track of a road in a controlled environment.
Conference Paper
Full-text available
El término " Internet de las cosas " , o IoT (Internet of Things), surgió en el Massachussetts Institute of Technology, y refiere a la inter-conexión M2M. IoT es un concepto novedoso que revoluciona la manera en la cual los dispositivos interaccionan y actual. Cuando nos referimos a este concepto, estamos hablando de la interacción que se produce entre diversos dispositivos físicos, actuadores, sensores con conexión a internet, y que permiten a esos objetos recopilar información e intercambiar datos. Estas interacciones se pueden producir tanto entre objetos y personas como entre objetos y otros objetos sin la mediación de usuarios. Los beneficios qué nos aporta tener todos los dispositivos conectados son muy variados, y van desde la agilización de tareas de la vida cotidiana, hasta el incremento de la productividad en grandes industrias. Este concepto puede ser empleado en el medio ambiente para la adquisición de datos de estos entornos y que puedan ser empleados en la mejora de cultivos, control de plagas, etc. Estos beneficios son debidos a la obtención de gran cantidad de datos, esta gran cantidad de datos no aportan nada nuevo si no los transformamos en información útil e interpretamos correctamente. Esta información, son pruebas, por lo que en un futuro la información que se aporte en los juicios por delitos medioambientales provendrá del concepto IoT (sensores, dispositivos, interconexión de máquinas).
Conference Paper
Full-text available
Smart cities are proposed as a medium-term option for all cities. This article aims to propose an architecture that allows cities to provide solutions to interconnect all their elements. The study case focuses in locating and optimized regulation of traffic in cities. However, thanks to the proposed structure and the applied algorithms, the architecture is scalable in size of the sensor network, in functionality or even in the use of resources. A simulation environment which is able to show the operation of the architecture in the same way that a real city would, is presented.
Article
Full-text available
Nowadays, cloud computing is revolutionizing the services provided through the Internet to adapt itself in order to keep the quality of its services. Recent research foresees the advent of a new discipline of agent-based cloud computing systems that can make decisions about adaption in an uncertain environment. This paper discusses the role of argumentation in the next generation of agreement technologies and its use in cloud computing environments.
Article
Full-text available
Monitoring and tracking people at home usually requires high cost hardware installations, which implies they are not affordable in many situations. This study/paper proposes a monitoring and tracking system for people with medical problems. A virtual organization of agents based on the PANGEA platform, which allows the easy integration of different devices, was created for this study. In this case, a virtual organization was implemented to track and monitor patients carrying a Holter monitor. The system includes the hardware and software required to perform: ECG measurements, monitoring through accelerometers and WiFi networks. Furthermore, the use of interactive television can moderate interactivity with the user. The system makes it possible to merge the information and facilitates patient tracking efficiently with low cost.
Conference Paper
Full-text available
A novel approach to the combination of a case based reasoning system and an artificial neural network is presented in which the neural network is integrated within the case based reasoning cycle so that its generalizing ability may be harnessed to provide improved case adaptation performance. The ensuing hybrid system has been applied to the task of oceanographic forecasting in a real-time environment and has produced very promising results. After presenting classifications of hybrid artificial intelligence problem-solving methods, the particular combination of case based reasoning and neural networks, as a problem-solving strategy, is discussed in greater depth. The hybrid artificial intelligence forecasting model is then explained and the experimental results obtained from trials at sea are outlined.
Article
Full-text available
Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the blockage of the satellite signals. However, accuracy in indoor RTLSs is still a problem requiring novel solutions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radiofrequency waves, such as attenuation, diffraction, reflection and scattering. These effects can lead to other undesired problems, such as multipath. When the ground is responsible for wave reflections, multipath can be modeled as the ground reflection effect. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the ground reflection effect by using multilayer perceptron artificial neural networks.
Article
Full-text available
This paper presents a case-based planning and beliefs, desires, intentions (CBP–BDI) planning model which incorporates a novel artificial neural network. The CBP–BDI model, which is integrated within an agent, is the core of a multi-agent system that allows managing the security in industrial environments. The BDI model integrates within a CBP engine of reasoning that incorporates artificial neural network-based techniques, and in this way it is possible to adapt past experiences to generate new plans. The proposed model uses self-organized maps to calculate optimum routes for the security guards. Besides, some technologies of ambient intelligence such as radio-frequency identification and Wi-Fi are used to develop the intelligent environment that has been tested and analysed in this paper.
Article
Full-text available
This work presents a system for automatically evaluating the interaction that exists between the atmosphere and the ocean's surface. Monitoring and evaluating the ocean's carbon exchange process is a function that requires working with a great amount of data: satellite images and in situ vessel's data. The system presented in this study focuses on computational intelligence. The study presents an intelligent system based on the use of case-based reasoning (CBR) systems and offers a distributed model for such an interaction. Moreover, the system takes into account the fact that the working environment is dynamic and therefore it requires autonomous models that evolve over time. In order to resolve this problem, an intelligent environment has been developed, based on the use of CBR systems, which are capable of handling several goals, by constructing plans from the data obtained through satellite images and research vessels, acquiring knowledge and adapting to environ-mental changes. The artificial intelligence system has been successfully tested in the North Atlantic Ocean, and the results obtained will be presented in this study.
Article
Full-text available
Microarray technology can measure the expression levels of thousands of genes in an experiment. This fact makes the use of computational methods in cancer research absolutely essential. One of the possible applications is in the use of Artificial Intelligence techniques. Several of these techniques have been used to analyze expression arrays, but there is a growing need for new and effective solutions. This paper presents a Case-based reasoning (CBR) system for automatic classification of leukemia patients from microarray data. The system incorporates novel algorithms for data mining that allow filtering, classification, and knowledge extraction. The system has been tested and the results obtained are presented in this paper.
Article
In the last ten years, social networks have had a great influence on people’s lifestyles and have changed, above all, the way users communicate and relate. This is why, one of the main lines of research in the field of social networks focuses on finding and analyzing possible connections between users. These developments allow users to expand on their network of contacts without having to search among the total set of users. However, there are many types of social networks which attract users with specific needs, these needs influence on the type of contacts users are looking for. Our article proposes a relationship recommender system for a business and employment-oriented social network. The presented system functions by extracting relevant information from the social network which it then uses to adequately recommend new contacts and job offers to users. The recommender system uses information gathered from job offer descriptions, user profiles and users’ actions. Then, different metrics are applied in order to discover new ties that are likely to convert into relationships.
Article
Optimization problems often require the use of optimization methods that permit the minimization or maximization of certain objective functions. Occasionally, the problems that must be optimized are not linear or polynomial; they cannot be precisely resolved, and they must be approximated. In these cases, it is necessary to apply heuristics, which are able to resolve these kinds of problems. Some algorithms linearize the restrictions and objective functions at a specific point of the space by applying derivatives and partial derivatives for some cases, while in other cases evolutionary algorithms are used to approximate the solution. This work proposes the use of artificial neural networks to approximate the objective function in optimization problems to make it possible to apply other techniques to resolve the problem. The objective function is approximated by a non-linear regression that can be used to resolve an optimization problem. The derivate of the new objective function should be polynomial so that the solution of the optimization problem can be calculated.
Conference Paper
Tinnitus is an annoying ringing in the ears, in varying shades and intensities. Tinnitus can affect a patient’s overall health and social well-being (e.g., sleep problems, trouble concentrating, anxiety, depression and inability to work). Usually, the diagnostic procedure of tinnitus passes through three steps, i.e., audiological examination, psychoacoustic measurement, and disability evaluation. All steps are performed by physicians, by using dedicated hardware/software and administering questionnaires. The paper reports on the results of a one-year running project whose aim is to directly support patients in such a diagnostic procedure by using a specific device and their smartphone.
Chapter
Today, there is a common trend to use tools and methodologies that allow the development of Multi-Agent Systems (MAS) with capabilities of reorganization and adaptation to determine changes in their environments. This work presents an architecture based on different levels and whose key level is the one corresponding to the semi-open type of MAS, structured in such a way that it is able to solve conflicts. In addition, a case study is introduced with the objective of showing the possibilities on conflict resolution basis, where a specifically designed architecture is utilized for that purpose. In particular, the system is applied to the resolution of the conflict raised by the decision of the technology to be used in order to obtain or to measure information in smart cities.
Conference Paper
It is undeniable that the term Cloud Computing has gained in importance at a remarkable pace. It is a technology which is becoming a common element of our life, due to the variety of devices related to the Internet of Things. In this technological frame, there are not many studies in which a Multiagent system has facilitated the management of a cloud-based computational environment; although a first sight its features (autonomy, decentralization, auto-organization, etc.) seem suitable for the task. This study presents the +Cloud which is a cloud platform managed by a Multiagent System.
Article
Context-aware systems are able to capture information from the context in which they are executed, assign a meaning to the gathered information, and change their behavior accordingly. As a result, the systems can offer services to users according to their individual situation within the context. This article analyzes the important aspects of context-aware computing such as capturing information for context attributes and determining the manner of interacting with users in the environment. Used in conjunction with mobile devices, context-aware systems are specifically used to improve the usability of applications and services. This article proposes the home care context-aware computing (HoCCAC) multiagent system that identifies and maintains a permanent fix on the location of patients in their home, and manages the infrastructure of services within their environment securely and reliably by processing and reasoning the data received. Based on the multiagent system, a prototype was developed to monitor patients in their home. The HoCCAC multiagent system uses a critical path method-based planning model that, in the present study, prepares the most optimal task-planning schedule for the patients in their home, is capable of reacting automatically when faced with dangerous or emergency situations, replanning any plans in progress and sending alert messages to the system. The results obtained with this prototype are presented in this article.
Article
This paper proposes a replanning mechanism for deliberative agents as a new approach to tackling the frame problem. We propose a beliefs desires and intentions (BDI) agent architecture using a case-based planning (CBP) mechanism for reasoning. We discuss the characteristics of the problems faced with planning where constraint satisfaction problems (CSP) resources are limited and formulate, through variation techniques, a reasoning model agent to resolve them. The design of the agent proposed, named MRP-Ag (most-replanable agent), will be evaluated in different environments using a series of simulation experiments, comparing it with others such as E-Ag (Efficient Agent) and O-Ag (Optimum Agent). Last, the most important results will be summarized, and the notion of an adaptable agent will be introduced.
Article
This paper introduces the SHOMAS Multiagent System that provides guidance on leisure facilities and suggestions for shopping in malls. The multiagent architecture incorporates reactive and deliberative agents that take decisions automatically. The developed deliberative agent provides suggestions in execution time, with the help of case-based planners. This agent is described together with its guidance and suggestion mechanism. SHOMAS has been tested successfully, and the results obtained are presented in this paper.
  • L Garcia-Ortiz
  • H Perez-Ramos
  • P Chamoso-Santos
  • J I Recio-Rodriguez
  • A Garcia-Garcia
  • J A Maderuelo-Fernandez
  • B Sanchez-Salgado
Garcia-Ortiz, L., Perez-Ramos, H., Chamoso-Santos, P., Recio-Rodriguez, J. I., Garcia-Garcia, A., Maderuelo-Fernandez, J. A.,... & Sanchez-Salgado, B. (2016). [PP. 08.02] AUTOMATIC IMAGE ANALYZER TO ASSESS RETINAL VESSEL CALIBER (ALTAIR) TOOL VALIDATION FOR THE ANALYSIS OF RETINAL VESSELS. Journal of Hypertension, 34, e160.