International Conference on Machine Learning and Applications Authors Sergiu Limboi, Mara Deac-Petrusel Abstract In the last years, a wide range of new similarity measures has been designed and applied to different contexts. Currently, there’s a deep lack in the validation and evaluation steps for novel similarities. In general, new measures are validated mostly through…
International Conference on Intelligent Tutoring Systems Authors A. Guran, G. Cojocar, L. Dioşan Abstract Education, like the large majority of domains, has been impacted by the rapid development of communications and technology. What was perceived before as an ideal, i.e., the enhancement of the learning process through modern techniques, now it has been rapidly…
Abstract An important problem in network science is finding relevant community structures in complex networks. A community structure is a partition of the network nodes into clusters or modules, such that each cluster is densely connected. Current community detection algorithms have time complexity, centralization, and scalability issues. In this paper, to solve this problem,…
Citare Marginean, R., Andreica, A., Diosan, L., Bálint, Z., Stochastic remote neighborhoods control GrowCut’s segmentation semanticsMECO45 45th Conference of the Middle European Cooperation in Statistical Physics , 2020
Abstract Education has suffered multiple changes due to technological progress. Even though the current generation of preschoolers (aged 3 to 6 years in our country) is called digital native, there is a lack of focus on introducing technology enabled learning tools for them. This paper presents our approach to designing smart learning experiences for…
Abstract This paper proposes a novel method for supervised optimization of cellular automata rules using curriculum learning. The optimized edge detector manages to generalize a rule from synthetic data that is applicable to magnetic resonance images, removing the need for manual annotation of medical data. The method achieves competitive results with classical edge detectors…
Abstract Children of nowadays grow in a digital landscape, so education has embraced the advantages brought by the multimedia technology progress. Appropriate interactive learning experiences positively influence learners’ performance. However, new challenges occur when the learners are preschoolers, as they are not able to articulate and communicate their experience towards interaction with edutainment applications.…
Abstract Facial Expression Recognition is a sub-branch of Affective Computing that specializes in extracting human emotions and facial features from visual input (images and videos) and tagging them to specific emotion hierarchies. The difficulty of this task lies not only in the subjectivity of distinguishing between human emotional states but, also in the diversity…
Abstract Edge detection is a fundamental image analysis task, as it provides insight on the content of an image. There are weaknesses in some of the edge detectors developed until now, such as disconnected edges, the impossibility to detect branching edges, or the need for a ground truth that is not always accessible. Therefore,…
Abstract Nowadays, when the changes that appear in programming paradigms and in software process development methodologies are extremely frequent, teaching a Software Engineering related course has become a demanding task. To all these are added changes caused by the dynamics of the society and the traits of the current learners and how they learn. …