Titlebook: Artificial Intelligence: Methods and Applications; 8th Hellenic Confere Aristidis Likas,Konstantinos Blekas,Dimitris Kalle Conference proce

傲慢人

Conference proceedings 2014re are 34 regular papers out of 60 submissions, in addition 5 submissions were accepted as short papers and 15 papers were accepted for four special sessions. They deal with emergent topics of artificial intelligence and come from the SETN main conference as well as from the following special sessio

草率男

grovel

文件夾

Forschungsdesign: Organisationsethnografie,) Deducing expressions to determine tolerances of camera misalignment for an acceptable inaccuracy of the system. This tool can be used by any 3D measuring system using a single camera. Resulting tolerances can be directly used for mechanical design of camera placement in the vision based inspection systems.

CRUC

Fehlermaskierung durch verteilte Systemeplete and efficient distributed reasoning. The proposed framework combines locality-based rules with graph-based modularization techniques using a generic constraint problem solving framework. The paper presents experimental results concerning the modularization task.

充氣女

Play Ms. Pac-Man Using an Advanced Reinforcement Learning Agentcess without the necessity of Q-function approximation. Several experiments were made using the multiagent MASON platform where we measured the ability of the approach to reach optimum generic policies which enhances its generalization abilities.

構想

seduce

Study the Effects of Camera Misalignment on 3D Measurements for Efficient Design of Vision-Based Ins) Deducing expressions to determine tolerances of camera misalignment for an acceptable inaccuracy of the system. This tool can be used by any 3D measuring system using a single camera. Resulting tolerances can be directly used for mechanical design of camera placement in the vision based inspection systems.

小步舞

Modularizing Ontologies for the Construction of , Distributed Knowledge Basesplete and efficient distributed reasoning. The proposed framework combines locality-based rules with graph-based modularization techniques using a generic constraint problem solving framework. The paper presents experimental results concerning the modularization task.

optic-nerve

Multi-view Regularized Extreme Learning Machine for Human Action Recognitionntation on three publicly available action recognition databases, where its performance has been compared with that of two commonly used video representation combination approaches, i.e., the vector concatenation before learning and the combination of classification outcomes based on learning on each view independently.