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Presented papers written in English and published in the Conference proceedings will be submitted for posting to IEEE Xplore.
| Authors are kindly asked to prepare presentations lasting no more than 10 minutes. |
| BiForD - Biometrics & Forensics & De-identification and Privacy Protection |
Invited Speech
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V. Struc (Faculty of Electrical Engineering, Ljubljana, Slovenia)
Face Alignment: Addressing Pose Variability in Face Recognition Systems |
Papers
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D. Sáez-Trigueros, H. Hertlein (University of Hertfordshire, Hatfield, United Kingdom), M. Hartnett (IDscan Biometrics Ltd, London, United Kingdom), L. Meng (University of Hertfordshire, Hatfield, United Kingdom)
Shape and Texture Combined Face Recognition for Detection of Forged ID Documents |
L. Meluch, I. Tokárová (Slovak University of Technology, Bratislava, Slovakia), P. Farkaš (Slovak University of Technology and Pan European University, Bratislava, Slovakia), F. Schindler ( Pan European University, Bratislava, Slovakia)
Simple Method Based on Complexity for Authorship Detection of Text |
Z. Sun, L. Meng (University of Hertfordshire, Hatfield, United Kingdom), X. Duan, Z. Tan (Aalborg University, Aalborg, Denmark), A. Ariyaeeinia (University of Hertfordshire, Hatfield, United Kingdom)
Privacy Protection Performance of De-identified Face Images with and without Background |
I. Filković, Z. Kalafatić, T. Hrkać (Fakultet elektrotehnike i računarstva, Sveučilište u Zagrebu, Zagreb, Croatia)
Deep Metric Learning for Person Re-Identification and De-Identification |
D. Marčetić, S. Ribarić (Faculty of Electrical Engineering and Computing, Zagreb, Croatia)
Deformable Part-based Robust Face Detection under Occlusion by Using Face Decomposition into Face Components |
P. Grd, M. Bača (Fakultet organizacije i informatike, Varaždin, Croatia)
Creating a Face Database for Age Estimation and Classification |
R. Singh, B. Raj, D. Gencaga (Carnegie Mellon University, Pittsburgh, United States)
Forensic Anthropometry from Voice: An Articulatory-Phonetic Approach |
| CIS 2016 |
Papers
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S. Carrato, S. Marsi, E. Medvet, F. Pellegrino, G. Ramponi, M. Vittori (University of Trieste, Trieste, Italy)
Computer Vision for the Blind: a Dataset for Experiments on Face Detection and Recognition 
For the needs of a research project that aims at developing vision-based techniques that assist the social interaction of a blind person, a dataset has been created. Two totally blind Users have acquired the sequences, using at the same time a glasses-mounted camera and a necklace-mounted one. The video sequences were acquired in different environments, selecting conditions in which a user could be interested in detecting the presence of some of his/her acquaintances, to approach them in a most natural way. The sequences have been temporally cropped to extract video shots that, by inspection, were deemed to contain events valuable for the goals of the project. The shots are presently being annotated, and some preliminary experiments on face detection have been performed on the annotated data. Overall, this task enabled the researchers and the users to make several observations about the specific application that is being considered.
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D. Solus, Ľ. Ovseník, J. Turán (Technical University of Košice, Košice, Slovakia)
Impact of Light Conditions on the Vertical Traffic Signs Detection in Vertical Traffic Signs Recognition System
This paper is focused on impact of light conditions on the vertical traffic signs detection in Vertical Traffic Signs Recognition System (VTSRS). VTSRS consists of two main phases – detection phase and recognition phase. The key task of a detection phase is to locate the area of the vertical traffic sign (ROI - Region of Interest) from the captured image of the real traffic. Detection phase might be based on three different methods – colour-based, shape-based and combination of both methods. The light conditions are affecting the success of each detection method. The detected ROIs are compared with the reference traffic sign by Optical Correlator in a recognition phase. Several experiments have been done by using of each detection method in different light conditions. Results and conclusion are discussed.
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D. Filko, E. Nyarko, R. Cupec (Faculty of Electrical Engineering, Osijek, Croatia)
Wound Detection and Reconstruction Using RGB-D Camera
The advent of inexpensive RGB-D sensors pioneered by the original Kinect sensor, has paved the way for a lot of innovations in computer and robot vision applications. In this article, we propose a system which uses the new Kinect 2 sensor in a medical application for the purpose of detection and 3D reconstruction of chronic wounds. Wound detection is based on a per block classification of wound tissue using color histograms and the nearest neighbor approach. The 3D reconstruction is similar to Kinectfusion where ICP is used for determining the rigid body transformation, color enhanced TSDF is applied for scene fusion, while the marching cubes algorithm is used for creating a surface mesh. The entire system is implemented in CUDA which enables real-time operation. The end result of the developed system is a precise 3D colored model which can be used for determining a correct therapy and treatment of chronic wounds.
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M. Horvat (Zagreb University of Applied Sciences, Zagreb, Croatia), K. Jednoróg, A. Marchewka (Nencki Institute of Experimental Biology, Warsaw, Poland)
Clustering of Affective Dimensions in Pictures: An exploratory analysis of the NAPS database
Photographs and other multimedia documents can easily provoke strong emotional reactions. While knowledge discovery based on semantics and visual properties of pictures is considerably explored, little attention is given to mining of affective features of visual stimuli. We report result from clustering of 1356 stimuli from the Nencki Affective Picture System database using two-dimensional (valence/arousal) model of affect and k-means unsupervised learning algorithm. Clustering with k=1–94 centroids is reported, together with dominant picture keywords and descriptive statistical parameters. Optimal number of centroids was estimated using minimum cumulative error rule. A custom Java application integrated with WEKA machine learning software was developed for the study. The results are freely available by contacting the first author. A practical goal of this research is to develop an intelligent expert system that could infer emotion content of multimedia from evaluation of its semantics, and vice versa, estimate dominant semantics from affect if such information is available. The system could potentially have many useful applications such as supported construction of affective multimedia databases, video recommendation or emotion estimation. Reported information on clustering of emotions is essential for success of such a system.
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Papers
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A. Budin (Ericsson Nikola Tesla, Zagreb, Croatia), S. Krajnović (Ericsson AB, Stockholm, Sweden)
Challenges in Adopting Big Data Strategies and Plans in Organizations
In today’s world, organizations of all types – be it in the industrial, governmental or non-governmental segments - are beginning to realize that embracing the full power and potential of big data and advanced analytics can bring significant benefits to their businesses and to the society in general. Technologies involved in big data analytics are already quite advanced and allow reaping the benefits of analytics results. However, many organizations are facing different issues in developing and adopting big data plans and strategies. Those issues can be internal and related to organizational challenges and the value of information, but they can also be related to regulatory and legal requirements. The focus of the paper will be on the above mentioned organizational and regulatory challenges, and not the technology related ones.
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S. Panwar, V. Upadhyay, S. Bishnoi (Govt. Engineering College Bikaner, Bikaner, India)
A survey of Intelligent System Techniques for Indian Stock Market Forecasting
Forecasting the movements of stock market is strenuous and noteworthy task for both the researchers and investors. The movements of stocks market is affected by local and global economic factors related to the market and political movements. In this field of research a substantial amount of knowledge regarding finance, statistics and Artificial Intelligence is needed to achieve good results. To perceive the movements of stock markets we need to interpret significant amount of information from the non-linear, volatile and non-parametric raw data. For reducing the complexity of stock market forecasting we need to extract some features from the raw data.
To make the task of stock market forecasting easier for researchers and traders we made a study about Indian stock market and also we have presented a complete summary report. In this summary report, we have been included 50 research articles related to Indian stock market with some highly cited articles related to other international markets.
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K. Andrić (Privredna Banka Zagreb, Zagreb, Croatia), D. Kalpić (Fakultet elektrotehnike i računarstva, Sveučilište u Zagrebu, Zagreb, Croatia)
The Effect of Class Distribution on Classification Algorithms in Credit Risk Assessment
This paper makes a practical contribution to classification in credit risk assessment by providing empirical evidence on which class distribution in the training sample should be used to maximize performance of different classification algorithms. Data used for credit risk assessment are often imbalanced due to the number of defaulting clients, who represent the minority class, being much less numerous than the non-defaulting majority class. Classification algorithms are usually biased towards the majority class and can show deceivingly high overall prediction accuracy, while at the same time exhibiting poor performance in prediction of the minority class. Although altering class distribution can be an effective method for alleviating the adverse impact of class imbalance, limited research efforts have been devoted to empirical evaluation of the role of class distribution in credit risk assessment, especially when dealing with real life data samples. To address this issue, an empirical study on the effect of different proportion of training examples belonging to each class on classifiers’ performance is presented. In addition to logistic regression, neural networks and gradient boosting methods were evaluated using several real life and publicly available datasets from the UCI Machine Learning Repository.
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E. Zunic, A. Djedovic (Info Studio Ltd, Sarajevo, Bosnia and Herzegovina), B. Zunic (Goethe-Institut B&H, Sarajevo, Bosnia and Herzegovina)
Software Solution for Optimal Planning of Sales Persons Work Based on Depth-First Search and Breadth-First Search Algorithms
This paper presents and describes the practical usage of DFS (Depth First Search) and BFS (Breadth First Search) algorithms in the planning and optimization of sales persons work. Experiments for optimal implementation of these two algorithms for planning purposes are made through a specially developed MATLAB simulator. The application consists of two parts: Web application and Mobile application. Web application developed using the Application Development Framework Technology (ADF), while for the development of the mobile version of application it's used Oracle ADF Mobile. Both applications are interactive with Google Maps, and based on the selected input parameters (such as the origin and destination of sales persons, the way of planning, any possible obstacles, etc.) visually show the results, indicators and analysis. The commercial version of the software, eSalesmanPlan, which uses the aforementioned algorithms used in several companies in Bosnia and Herzegovina. All indicators point to significant savings both in human as well as financial resources and it will be also presented.
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E. Bytyci, K. Sylejmani, A. Dika (University of Prishtina, Prishtina, Kosovo)
Iterated Local Search Algorithm for Planning the Sequence of Arrivals and Departures at Airport Runways
In this paper, in order to tackle one of the dozens of the challenging optimization problems in aviation industry, we introduce an algorithm for planning the sequence of arrivals and departures of aircraft in a runway. The algorithm is based in Iterated Local Search algorithm and uses two effective operators, namely swap and shift, for exploring the neighborhood of current running solution. The experiments that are conducted with real instances show that this approach achieves better results than the First Come First Served approach, while computing the results in relatively short period of time, which is in order of milliseconds.
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I. Britvić, A. Nikitović (Visoka škola za informacijske tehnologije, Zagreb, Croatia)
Energy Efficiency with Intelligent Light Management Systems
Improving our energy efficiency is one of the most important technology goals set by EU Horizon 2020 agenda. Significant amount of energy is wasted in usage of sub-optimal lighting in home and especially in commercial sector.
This paper analyses recent developments in market of intelligent light systems as well as in Internet of Things technologies that could be utilized to achieve light savings. Solutions of leading light management system vendors are reviewed and their strong and weak points are listed.
Paper describes minimal requests for mathematical algorithms and offers practical guidelines and approaches for future development in light management area.
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M. Klarić (DALEKOVOD d.d., ZAGREB, Croatia), I. Kuzle (FAKULTET ELEKTROTEHNIKE I RAČUNARSTVA, ZAGREB, Croatia), I. Livaja (Polytechnic of Sibenik, Šibenik, Croatia)
Adaptive and modular urban smart infrastructure
More and more countries and regions are trying to develop smart city projects in order to make transformation to cognitive and sensible cities and municipalities. Parallel to this process the aging of existing infrastructure also makes huge demands to public budgets regarding the need for large capital investments in reconstruction or maintenance. Latest developments in information and communication (ICT) industry created also large space for new kind of infrastructure very suitable for additional services as well as for update of existing ones. In this paper one solution of cost optimizing is described through reconstruction and expansion of public lighting systems connected with several static and dynamic ICT installations. These, existing infrastructures can be used as a basic platform where all additional IoT installations can fast and easily be done modularly and adaptively.
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V. Rishiwal (MJP Rohilkhand University, Bareilly, India), H. Khan (Tejas Networks, Bangalore, India)
Automatic Pothole and Speed Breaker Detection Using Android System
Recent studies have shown that road surface monitoring is essential for the municipal corporations as well as for travelers for choosing the best road possible. This paper describes the algorithm for automatic detection of potholes and speed breakers along with their co-ordinates. A database is maintained for each road, which is made available to the public with the help of global database or through a portal. Potholes and speed breakers are detected using android’s built-in accelerometer along with their severity. The accuracy of the algorithm came out to be 93.75% for detection of potholes and speed breakers. This is a cost efficient and very effective system of road surface monitoring
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D. Brodic, S. Petrovska, M. Jevtic, Z. Milivojević (University of Belgrade, Bor, Serbia)
The Influence of the CAPTCHA Types to Its Solving Times
In this paper, we present a survey of different CAPTCHA types. Then we address the problem of the CAPTCHA userability. In the experiment, the Internet user response to solve different types of CAPTCHA is tested. The obtained results are given and statistically processed. They are discussed leading to the conclusion different types of CAPTCHA usability and suitability for Internet users.
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S. Lugovic (Zagreb University of Applied Sciences, Department of Computer Science and Information Technology, Vr, Zagreb, Croatia), I. Dunđer (University of Zagreb, Faculty of Humanities and Social Sciences, Department of Information and Commu, Zagreb, Croatia), M. Horvat (Zagreb University of Applied Sciences, Department of Computer Science and Information Technology, Vr, Zagreb, Croatia)
Techniques and Applications of Emotion Recognition in Speech
Affective computing opens a new area of research in computer science with the aim to improve the way how humans and machines interact. Recognition of human emotions by machines is becoming a significant focus in recent research in different disciplines related to information sciences and Human-Computer Interaction (HCI). In particular, emotion recognition in human speech is important, as it is the primary communication tool of humans. This paper gives a brief overview of the current state of the research in this area with the aim to underline different techniques that are being used for detecting emotional states in vocal expressions. Furthermore, approaches for extracting speech features from speech datasets and machine learning methods with special emphasis on classifiers are analysed. In addition to the mentioned techniques, this paper also gives an outline of the areas where emotion recognition could be utilised, such as healthcare, psychology, cognitive sciences and marketing.
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I. Dunđer (University of Zagreb, Faculty of Humanities and Social Sciences, Department of Information and Commu, Zagreb, Croatia), M. Horvat, S. Lugovic (Zagreb University of Applied Sciences, Department of Computer Science and Information Technology, Zagreb, Croatia)
Word Occurrences and Emotions in Social Media: Case Study on a Twitter Corpus
Twitter is currently the most popular tool for social interaction and real-time information exchange. Outreach and importance of individual accounts is measured by the number of their followers. The aim of this paper is to investigate the applicability and usefulness of corpora containing textual and visual information for the purpose of machine observation of Twitter activities. The results in the presented analytic research are based on a dataset of more than 16000 tweets collected from 22 startup founders’ Twitter accounts with a large number of followers over a four-month period. Word usage in tweets was examined with natural language processing (NLP) techniques, applying word occurrence analyses and a manual qualitative evaluation of the most frequent words within the dataset, primarily focusing on the distribution of words. Furthermore, profile pictures of Twitter accounts were collected in order to conduct a facial emotion analysis and emotion mining. Estimated basic emotional states were statistically compared with the number of tweets posted and the number of new followers gained during the observed timespan.
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S. Kochemazov, A. Semenov, O. Zaikin (Matrosov Institute for System Dynamics and Control Theory of Siberian Branch of Russian Academy of S, Irkutsk, Russian Federation)
The Application of Parameterized Algorithms for Solving SAT to the Study of Several Discrete Models of Collective Behaviour
In this paper we present the computational study of one class of discrete models of collective behavior. In the context of these models a set of agents, that form a collective, is represented by a network. Each agent is assigned a special weight function. The behavior of a collective in discrete time moments is specified with a vector function, the coordinates of which are defined by values of agents weight functions at corresponding time moments. We study phenomena concerning the so-called conforming behavior: when an agent at some time moment decides to act or not to act depending on the similar decisions made by agents from its neighborhood at the previous moment. We consider the problem how to dispose a relatively small number of always acting agents called instigators in the network so that the majority of agents soon become active. We apply state-of-the-art SAT solvers to this problem. To tune the solver we use special parametrization techniques. In our computational experiments we show that the solving of considered problems of large dimension can be significantly sped up by finding effective sets of SAT solver parameters on test instances from the same class but of much lower dimension.
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N. Nagul (Institute for System Dynamics and Control Theory, Irkutsk, Russian Federation)
Logical-Algebraic Equations Application in Discrete-Event Systems Studying
The paper shows an application of the method of logical-algebraic equations (LAE-method) to the study of properties of controlled discrete-event systems (DESs). To apply the method we treat a property of the system under consideration as a property of an algebraic system. Then the algorithm for construction the conditions of preservation of properties of many-sorted algebraic systems in terms of morphisms is exploited. We address the issue of applying the LAE-method to study properties of partially observed DES. Using the LAE-method, we examine preservation of some essential properties of the generated language and demonstrate how the studying of DES with state observation can easily be reduced to the same problem in the context of event observation.
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N. Vlahović (Faculty of Economics University of Zagreb, Zagreb, Croatia)
An Evaluation Framework and a Brief Survey of Decision Tree Tools
Over the last 50 years decision trees have been extensively used in numerous application areas by practitioners and academics alike. Decision trees are both a mathematical representation tool and a highly versatile graphic representation tool suited for modelling and visualisation of structured hierarchical concepts. Decision tree construction algorithms belong to supervised learning algorithms in the field of machine learning. Most prominent applications areas of decision trees are managerial sciences, knowledge engineering and data analysis. Variety of specific decision tree types is used: decision analysis trees, knowledge representation trees, classification and regression trees, decision forests, etc. Software tools for each of these types are available often borrowing from one decision tree concept to another. As a consequence, distinct features and capabilities of these tools make direct comparison difficult. Goal of this paper is to propose a framework for evaluation of available decision tree tools in relation to their foundation model. Brief survey of currently available decision tree tools will be given accordingly. Results may motivate more comprehensible studies of decision tree applications. Results may also motivate development of hybrid decision tree tools where sound combination of decision tree concepts can enhance functionalities and provide additional benefits to users.
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E. Cherkashin, A. Davydov, A. Larionov (Matrosov Institute for System Dynamics and Control Theory of Siberian Branch of Russian Academy of S, Irkutsk, Russian Federation)
Positive Constructed Formulas Preprocessing for Automatic Deduction
The preprocessing of positively–constructed formulas (PCFs) for automatic deduction search algorithms is considered in this paper. A new efficient algorithm for conversion of the predicate calculus language formulas to the language of PCFs and equivalent rules of reducing PCFs, preserving the original heuristic structure of knowledge represented by the formulas of the predicate calculus language, are presented.
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R. Kudelić, D. Oreški, M. Konecki (FOI, Varaždin, Croatia)
Monte-Carlo Randomized Algorithm: Empirical Analysis on Real-world Information System
Determination of development priority of Information System subsystems is a problem that warrants resolution during Information System development. It has been proven, previously, that this problem of Information System Development Order is in fact NP-complete, NP-hard, and APX-hard. To solve this problem on a general case we have previously developed Monte-Carlo randomized algorithm, calculated complexity of this algorithm, and so on. After previous research we were able to come into possession of graphs that represent real-world Information Systems. Therefore, in this paper we will empirically analyse Monte-Carlo algorithm to determine how the algorithm works on real-world examples. Also, we will critically review the results and give some possible areas of future research as well.
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A. Mikhailov, A. Hmelnov, E. Cherkashin, I. Bychkov (Institute of System Dynamics and Control Theory at Siberian brance of Russian Acdemy of sciences, Irkutsk, Russian Federation)
Control Flow Graph Visualization in Compiled Software Engineering
Engineering of the compiled software is an important task in software engineering. One of the stages of the engineering technologies is a construction and analysis of a control flow graphs, which reflect a general structure of algorithms. The paper presents a technique for analyzing and visualizing the control flow graph of a compiled software. The analysis is based on semantically equivalent transformations of the original graph resulting in an abstract node that contains a hierarchy of isolated regions, which then associated with predefined templates resulting a graphical representation. The templates and additional signature data allow one to recognize the high-level programming structures and user statements to construct a flow-chart notation of the original program.
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T. Rolich, D. Domović (Tekstilno-tehnološki fakultet, Zagreb, Croatia), M. Golub (Faculty of Electrical Engineering and Computing, Zagreb, Croatia)
Bottom-Left and Sequence Pair for Solving Packing Problems
Nesting problem is a combinatorial optimization problem with a goal of placing a set of polygons within container boundaries without overlapping. If polygons in shape of cutting patterns are used, and the container has a fixed width, the problem is defined as a strip-packing problem.
In this paper two methodologies are described: Bottom-Left (BL) and Sequence Pair (SP). Bottom-left is order based strategy which can solve strip-packing problem. It moves each polygon as far as possible to the bottom of the temporary layout and then as far as possible to the left. A valid position is found when a polygon collides with the partial layout at its lower and left side. Sequence pair is an abstract representation method for nesting problem that creates a relationship model between bounding box approximations of polygons instead of direct placement.
The goal of the research is to compare the methodologies, as well as layout density obtained during experiments. Experiments have been conducted on benchmark datasets: Albano (24 parts), Marques (24 parts), Mao (20 parts) and Dagli (30 parts) in MATLAB environment, with BL performing 79.59, 79.02, 71.30 and 71.34 percent respectively (in average), and SP performing 74.66, 75.54, 66.24 and 75.54 percent respectively (in average).
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M. Pobar, M. Ivašić-Kos (Odjel za informatiku Sveučilište u Rijeci, RIJEKA, Croatia)
Automatic Image Annotation Refinement
Automatic image annotation methods automatically assign labels to images in order to facilitate tasks such as image retrieval, search, organizing and management. Incorrect labels may negatively influence the search results so image annotation should be as accurate as possible. Labels pertaining to objects or to whole scenes are commonly used for image annotation, and precision is especially important in case when scene labels are inferred from objects, as errors in the object labels may propagate to the scene level. One way to improve the annotation precision is by detecting and discarding the automatically assigned object labels that do not fit the context of other detected objects. This procedure is referred to as annotation refinement. Here, an approach to detection of likely incorrect labels based on the context of other labels and prior knowledge about mutual occurrence of various objects in images is tested.
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B. Okreša Đurić, M. Schatten (Fakultet organizacije i informatike, Varaždin, Croatia)
Defining Ontology Combining Concepts of Massive Multi-Player Online Role Playing Games and Organization of Large-Scale Multi-Agent Systems
Large-scale multi-agent systems (LSMAS) are becoming ever more popular and needed in the world of growing number of computer agents incorporated in gadgets used by people in all areas of life. Organization is therefore a very relevant concept in research on LSMAS, as the mentioned agents are expected to cooperate, and share information, hence improving quality of peoples' life. An example application domain of LSMAS are massive multi-player online games (MMOG), and their specific genre – MMO role-playing games (MMORPG). MMORPGs provide us with the opportunity to study both large-scale virtual interaction of players (agents), and coordination of large-scale distributed artificial intelligence. In this paper, we will present ontology of organization concepts, suited for LSMAS, merged with an ontology containing elements of a specific MMORPG. Combining these two ontologies into a comprehensive one, at the same moment paying attention to identified elements and aspects of organization, is going to present us with basis for an LSMAS structure which follows organizational constraints.
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M. Đurasević, D. Jakobović (Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia)
Comparison of Solution Representations for Scheduling in the Unrelated Machines Environment
Most scheduling problems belong to the class of NP hard problems. Because of that, heuristic search based approaches are often used in order to find solutions for scheduling problems. In this paper we compare several search based approaches for finding solutions to the unrelated scheduling problem. We define two different solution representations for the aforementioned problem and the representations are compared with each other. The first representation is a standard one for scheduling problems, which encodes solutions in the form of a permutation vector. The second representation, which we propose, uses a vector of floating point numbers to represent a schedule. The results of the search approaches are compared to several existing constructive heuristics developed especially for solving the unrelated machines scheduling problem. We also perform a complexity analysis of the search based approaches, in which we compute the time needed for them to outperform the problem specific heuristics.
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Basic information:
Chairs:
Slobodan Ribarić (Croatia), Andrea Budin (Croatia)
International Program Committee Chairman:
Petar Biljanović (Croatia)
International Program Committee:
Slavko Amon (Slovenia), Vesna Anđelić (Croatia), Michael E. Auer (Austria), Mirta Baranović (Croatia), Almir Badnjevic (Bosnia and Herzegovina), Bartosz Bebel (Poland), Ladjel Bellatreche (France), Eugen Brenner (Austria), Andrea Budin (Croatia), Željko Butković (Croatia), Željka Car (Croatia), Matjaž Colnarič (Slovenia), Alfredo Cuzzocrea (Italy), Marina Čičin-Šain (Croatia), Marko Delimar (Croatia), Todd Eavis (Canada), Maurizio Ferrari (Italy), Bekim Fetaji (Macedonia), Tihana Galinac Grbac (Croatia), Paolo Garza (Italy), Liljana Gavrilovska (Macedonia), Matteo Golfarelli (Italy), Stjepan Golubić (Croatia), Francesco Gregoretti (Italy), Stjepan Groš (Croatia), Niko Guid (Slovenia), Yike Guo (United Kingdom), Jaak Henno (Estonia), Ladislav Hluchy (Slovakia), Vlasta Hudek (Croatia), Željko Hutinski (Croatia), Mile Ivanda (Croatia), Hannu Jaakkola (Finland), Leonardo Jelenković (Croatia), Dragan Jevtić (Croatia), Robert Jones (Switzerland), Peter Kacsuk (Hungary), Aneta Karaivanova (Bulgaria), Mladen Mauher (Croatia), Igor Mekjavic (Slovenia), Branko Mikac (Croatia), Veljko Milutinović (Serbia), Vladimir Mrvoš (Croatia), Jadranko F. Novak (Croatia), Jesus Pardillo (Spain), Nikola Pavešić (Slovenia), Vladimir Peršić (Croatia), Tomislav Pokrajcic (Croatia), Slobodan Ribarić (Croatia), Janez Rozman (Slovenia), Karolj Skala (Croatia), Ivanka Sluganović (Croatia), Vlado Sruk (Croatia), Uroš Stanič (Slovenia), Ninoslav Stojadinović (Serbia), Jadranka Šunde (Australia), Aleksandar Szabo (Croatia), Laszlo Szirmay-Kalos (Hungary), Davor Šarić (Croatia), Dina Šimunić (Croatia), Zoran Šimunić (Croatia), Dejan Škvorc (Croatia), Antonio Teixeira (Portugal), Edvard Tijan (Croatia), A Min Tjoa (Austria), Roman Trobec (Slovenia), Sergio Uran (Croatia), Tibor Vámos (Hungary), Mladen Varga (Croatia), Marijana Vidas-Bubanja (Serbia), Boris Vrdoljak (Croatia), Damjan Zazula (Slovenia)
Registration / Fees:
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REGISTRATION / FEES
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Price in EUR
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Before May 16, 2016
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After May 16, 2016
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| Members of MIPRO and IEEE |
180
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200
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| Students (undergraduate and graduate), primary and secondary school teachers |
100
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110
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| Others |
200
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220
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Contact:
Slobodan Ribarić
Faculty of Electrical Engineering and Computing
Unska 3
HR-10000 Zagreb, Croatia
Phone: +385 1 612 99 52
Fax: +385 1 612 96 53
E-mail: slobodan.ribaric@fer.hr
Andrea Budin
Ericsson Nikola Tesla Inc.
Krapinska 45
HR-10000 Zagreb, Croatia
Phone:+385 1 365 34 23
Fax: +385 1 365 3548
E-mail: andrea.budin@ericsson.com
Location:
 Opatija, with its 170 years long tourist tradition, is the leading seaside resort of the Eastern Adriatic and one of the most famous tourist destinations on the Mediterranean. With its aristocratic architecture and style Opatija has been attracting renowned artists, politicians, kings, scientists, sportsmen as well as business people, bankers, managers for more than 170 years.
The tourist offering of Opatija includes a vast number of hotels, excellent restaurants, entertainment venues, art festivals, superb modern and classical music concerts, beaches and swimming pools and is able to provide the perfect response to all demands.
Opatija, the Queen of the Adriatic, is also one of the most prominent congress cities on the Mediterranean, particularly important for its international ICT conventions MIPRO that have been held in Opatija since 1979 gathering more than a thousand participants from more than forty countries. These conventions promote Opatija as the most desirable technological, business, educational and scientific center in Southeast Europe and the European Union in general.
For more details please look at www.opatija.hr/ and www.opatija-tourism.hr/.
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