Abstract Multi-robot path planning has evolved from research to real applications in warehouses and other domains; the knowledge on this topic is reflected in the large amount of related research published in recent years on international journals. The main focus of existing research relates to the generation of efficient routes, relying the collision detection…
Abstract Model View Controller (MVC) is one of the most widespread and used software architecture in client-side software. We are interested in automatically inferring and analyzing MVC architectures from mobile application codebases that could help to identify the architectural problems earlier in the development process, offering insightful knowledge for both software developers, architects, and…
Abstract Mobile applications are one of the most used pieces of software nowadays, as they continue to expand, the architecture of those software systems becomes more important. In the fast-paced domain of the mobile world, the applications need to be developed rapidly and they need to work on a wide range of devices. Moreover,…
Abstract In the last few years, we have seen an increase in the number of mobile applications and their usage. The architectural pattern and correctness represent a major factor in the success of a mobile project and its lifecycle. Since architectural patterns can not be imposed on a codebase without an external validation system,…
Abstract Image processing applications include image classification, image segmentation, image synthesis and many others. Each such task depends on extracting an effective set of features to characterize the images, and texture analysis has proven to output some of the most valuable features. For this reason, image texture analysis has been an actively researched topic…
Abstract Decision trees are some of the most popular and intuitive classification techniques. Based on the recursive division of the data, the goal is to ultimately identify regions in the space in which most instances belong to the same class. This paper proposes a game-theoretic decision tree using a two-player game to determine the…
Abstract Decision trees and random forests are some of the most popular machine learning tools for binary classification, being used in many practical applications. Both methods provide a neighborhood for tested data during the prediction phase, and probabilities are usually computed based on the proportion of classes in those neighborhoods. The approach presented in…
Abstract Cooperative-competitive social group dynamics may be modelled with multi-agent environments with a large number of agents from a few distinct agent-types. Even the simplest games modelling social interactions are suitable to analyze emerging group dynamics. In many cases, the underlying computational problem is NP-complex, thus various machine learning techniques are implemented to accelerate…
Abstract Breast cancer is the most commonly diagnosed type of cancer. It is essential to classify patients as quickly as possible into groups with a high or low risk of cancer, to provide adequate treatment. This paper aims to address the impact of the parameters of convolutional neural networks in the binary classification of…
Abstract Breast cancer causes numerous deaths worldwide; yet the numbers have decreased in the past years as a result of computer-aided diagnosis and proper treatment. The current paper is addressed to the base of such diagnosis system: pre-processing and segmentation. After a robust pre-processing, an unsupervised version of GrowCut is applied to define the…