Convolutional Neural Networks (CNNs) can provide accurate object classification. They can be extended to perform object detection by iterating over dense or selected proposed object regions. However, the runtime of such detectors scales as the total number and/or area of regions to examine per image, and training such detectors may be prohibitively slow. However, for some CNN classifier topolog...

This paper reviews a competent Pittsburgh LCS that automatically mines important substructures of the underlying problems and takes problems that were intractable with firstgeneration Pittsburgh LCS and renders them tractable. Specifically, we propose a χ-ary extended compact classifier system (χeCCS) which uses (1) a competent genetic algorithm (GA) in the form of χ-ary extended compact geneti...

in the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. in this study, hydrodynamic coefficients of an autonomous un...

In this paper, we take the advantages of extended superquadrics to represent and recognize the entire set of 36 geons. Extended superquadrics are novel volumetric shape models that include superquadrics as a special case. An extended superquadric model can be deformed in any direction because it extends the exponents of the superquadric model from constants to functions of the latitude and long...

Impetuous development of artificial neural networks makes it possible to transfer many ideas from this area into adjacent areas. This work investigates an opportunity of mapping learning classifier systems (LCS) into artificial neural networks (ANN). Possible learning types for hybrid connectionist classifier system (CLCS) for multi-step problems are derived. Transformation’s opportunity of the...

Due to increasing incidents of cyber attacks, building effective Intrusion Detection Systems (IDS) are essential for protecting information systems security, and yet it remains an elusive goal and a great challenge. Current IDS examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or low importance during detection process. The purpose of this s...

This paper proposes a competent Pittsburgh LCS that automatically mines important substructures of the underlying problems and takes problems that were intractable with first-generation Pittsburgh LCS and renders them tractable. Specifically, we propose a χ-ary extended compact classifier system (χeCCS) which uses (1) a competent genetic algorithm (GA) in the form of χ-ary extended compact gene...

Advancements in learning classifier system (LCS) algorithms have highlighted their unique potential for tackling complex, noisy problems, as found in bioinformatics. Ongoing research in this domain must address the challenges of modeling complex patterns of association, systems biology (i.e. the integration of different data types to achieve a more holistic perspective), and ‘big data’ (i.e. sc...