Innovations in Applied Artificial Intelligence: 18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2005, Bari, Italy, June 22-24, 2005, ProceedingsFloriana Esposito “Intelligent systems are those which produce intelligent o?springs.” AI researchers have been focusing on developing and employing strong methods that are capable of solving complex real-life problems. The 18th International Conference on Industrial & Engineering Applications of Arti?cial Intelligence & Expert Systems (IEA/AIE 2005) held in Bari, Italy presented such work performed by many scientists worldwide. The Program Committee selected long papers from contributions presenting more complete work and posters from those reporting ongoing research. The Committee enforced the rule that only original and unpublished work could be considered for inclusion in these proceedings. The Program Committee selected 116 contributions from the 271 subm- ted papers which cover the following topics: arti?cial systems, search engines, intelligent interfaces, knowledge discovery, knowledge-based technologies, na- ral language processing, machine learning applications, reasoning technologies, uncertainty management, applied data mining, and technologies for knowledge management. The contributions oriented to the technological aspects of AI and the quality of the papers are witness to a research activity clearly aimed at consolidating the theoretical results that have already been achieved. The c- ference program also included two invited lectures, by Katharina Morik and Roberto Pieraccini. Manypeoplecontributedindi?erentwaystothesuccessoftheconferenceand to this volume. The authors who continue to show their enthusiastic interest in applied intelligence research are a very important part of our success. We highly appreciate the contribution of the members of the Program Committee, as well as others who reviewed all the submitted papers with e?ciency and dedication. |
From inside the book
Page 29
... active contours. Indeed we can derive many aspects of these models as special cases of region competition [8, 9]. Active contours can be a special case in which there are two regions (object region Ro and background region Rb) and a ...
... active contours. Indeed we can derive many aspects of these models as special cases of region competition [8, 9]. Active contours can be a special case in which there are two regions (object region Ro and background region Rb) and a ...
Page 30
... active contours, the search area for optimal boundary curve is restricted to the narrow band around curve. This not ... active contours for distribution tracking proposed by Freedman et al. [2]. Freedman's method finds the region such ...
... active contours, the search area for optimal boundary curve is restricted to the narrow band around curve. This not ... active contours for distribution tracking proposed by Freedman et al. [2]. Freedman's method finds the region such ...
Page 31
... active contours. The Chamfer distances of the two methods are shown in Fig. 3. In the case of the proposed method, object localization using mean shift is considered as the first iteration. The distance in the proposed ... Active Contours 31.
... active contours. The Chamfer distances of the two methods are shown in Fig. 3. In the case of the proposed method, object localization using mean shift is considered as the first iteration. The distance in the proposed ... Active Contours 31.
Page 32
... active contours detect whole local optima passed by curve during curve evolution but the proposed method moves the initial curve near the global optimum using mean shift algorithm before curve evolution. 0 5 40 35 30 Freedman's method ...
... active contours detect whole local optima passed by curve during curve evolution but the proposed method moves the initial curve near the global optimum using mean shift algorithm before curve evolution. 0 5 40 35 30 Freedman's method ...
Page 33
... active contours is that the search areas for optima are limited to the narrow band around curve. Because of it, the active contours have difficulties to track objects that have large amount of motion. The other side, in the proposed ...
... active contours is that the search areas for optima are limited to the narrow band around curve. Because of it, the active contours have difficulties to track objects that have large amount of motion. The other side, in the proposed ...
Contents
1 | |
16 | |
19 | |
36 | |
55 | |
69 | |
Robust Character Segmentation System for Korean Printed Postal | 82 |
FeatureTableBased Automatic Question Generation for TreeBased | 95 |
Endoscopy Images Classification with Kernel Based Learning | 400 |
Minimum Spanning Trees in Hierarchical Multiclass Support Vector | 422 |
Intelligent Bayesian Classifiers in Network Intrusion Detection | 445 |
An Application in Public Health Care | 459 |
A DomainIndependent Approach to DiscourseLevel Knowledge | 470 |
A Meteorological Conceptual Modeling Approach Based on Spatial | 490 |
Mining Information Extraction Rules from Datasheets Without | 510 |
Genetic Algorithms | 524 |
DistanceBased Dynamic Interaction of Humanoid Robot with Multiple | 111 |
Robot Competition Using Gesture Based Interface | 131 |
Feasibility of Multiagent Simulation for the Trust and Tracing Game | 145 |
Reliable Multiagent Systems with Persistent PublishSubscribe | 165 |
Automated Teleoperation of WebBased Devices Using Semantic | 185 |
Plan Execution in Dynamic Environments | 208 |
Structural Advantages for Ant Colony Optimisation Inherent | 218 |
New Upper Bounds for the Permutation Flowshop Scheduling Problem | 232 |
Automatic Word Spacing in Korean for Small Memory Devices | 249 |
Haptic Fruition of 3D Virtual Scene by Blind People | 269 |
Towards Effective Adaptive Information Filtering Using Natural | 290 |
Discovering Learning Paths on a Domain Ontology Using Natural | 310 |
A Geometric Approach to Automatic Description of Iconic Scenes | 315 |
Reasoning | 321 |
Inferring DefiniteClause Grammars to Express Multivariate Time Series | 332 |
Obtaining a Bayesian Map for Data Fusion and Failure Detection | 342 |
Event Handling Mechanism for Retrieving Spatiotemporal Changes | 353 |
Freeway Traffic Qualitative Simulation | 360 |
PredictionBased Diagnosis and Loss Prevention Using ModelBased | 367 |
Classification of Ophthalmologic Images Using an Ensemble of Classifiers | 380 |
Application of a Genetic Algorithm to Nearest Neighbour Classification | 544 |
Hardware Architecture for Genetic Algorithms | 554 |
Predicting Construction Litigation Outcome Using Particle Swarm | 571 |
A SOM Based Approach for Visualization of GSM Network Performance | 588 |
Canonical Decision Model Construction by Extracting the Mapping | 609 |
Decision Support and Heuristic Search | 619 |
A SwarmBased | 638 |
Search on Transportation Network for LocationBased Service | 657 |
A New Crowded Comparison Operator in Constrained Multiobjective | 678 |
PoseInvariant Face Detection Using EdgeLike Blob Map and Fuzzy | 695 |
A Fuzzy LogicBased Approach for Detecting Shifting Patterns | 705 |
OWL Ontology Merging and Alignment Tool for the Semantic | 722 |
Complementing Search Engines with Text Mining | 743 |
Building Intelligent | 762 |
A Case Study | 783 |
A Nurse Scheduling System Based on Dynamic Constraint Satisfaction | 799 |
CaseBased Reasoning for Financial Prediction | 839 |
A Support Method for Qualitative SimulationBased Learning System | 851 |
Other editions - View all
Innovations in Applied Artificial Intelligence: 18th International ... Floriana Esposito Limited preview - 2005 |
Innovations in Applied Artificial Intelligence: 18th International ... Floriana Esposito No preview available - 2005 |
Common terms and phrases
Abstract active contours agent analysis application approach architecture Artificial Intelligence association rules automatically behavior Berlin Heidelberg 2005 blank nodes classifier cognitive components Computer concept constraints context data mining database dataset decision defined described detection distribution domain dynamic Engineering environment Esposito Eds evaluation example experiments extraction function fuzzy genetic algorithm goal graph haptic IEA/AIE IEEE implementation input interaction interface knowledge Machine Learning mereology method model checking module multi-agent systems neural networks neurons nodes objects obtained ontology operators optimal output paper parameters patterns performance pheromone pixel problem Proc proposed query recognition region representation represented reviewers robot scheduling Section selected semantic Semantic Web sensor sequences simulation solution spatial specific speech recognition Springer-Verlag Berlin Heidelberg structure Support Vector Machines techniques Technology tion tracking traffic variables vector