Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
A class of techniques in computer vision and graphics is based on capturing multiple images of a scene under different illumination conditions. These techniques explore variations...
One approach for evolutionary algorithms (EAs) to address dynamic optimization problems (DOPs) is to maintain diversity of the population via introducing immigrants. So far all imm...
In recent years, optimization in dynamic environments has attracted a growing interest from the genetic algorithm community due to the importance and practicability in real world a...
: Wireless control systems (WCSs) often have to operate in dynamic environments where the network traffic load may vary unpredictably over time. The sampling in sensors is conventi...
Abstract. Autonomous agents are systems situated in dynamic environments. They pursue goals and satisfy their needs by responding to external events from the environment. In these ...
The development of many highly dynamic environments, like pervasive environments, introduces the possibility to use geographically closely-related services. Dynamically integrating...
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its importance in real-world applications. Several app...
One of the most difficult problems in Multi-Agent Systems (MAS) involves representing the knowledge and beliefs of an agent which performs its tasks in a dynamic environment. New p...
—In highly dynamic environments like academy and industry it is becoming essential the need of efficient systems for resources organization and discovery. In this paper we descr...