The purpose of this work is to study the possible approaches to build a recommendation system that could help students in organizing their work and improving their results. More specifically, we intend to predict grades of a student for future exams, based on his/her previous results and the past grades received by all students…
Proteins are essential molecules, that must correctly perform their roles for the good health of living organisms. The majority of proteins operate in complexes and the way they interact has pivotal influence on the proper functioning of such organisms. In this study we address the problem of protein–protein interaction and we propose and investigate…
Fall detection (FD) has been the focus of many research studies during the last years. Developing reliable FD systems is relevant, for instance, to provide support to the elderly population in their everyday life. Besides, the generalization of the use of wearable devices (and more specifically, on-wrist devices) to measure the daily activity strongly…
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
We present a new type of optimization algorithms, adapted for neural network training. These algorithms are based upon sequential operator splitting technique for some associated dynamical systems. Furthermore, we investigate through numerical simulations the empirical rate of convergence of these iterative schemes toward a local minimum of the loss function, with some suitable choices…
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 on…
Edge detection is an important component in many computer vision tasks since edges convey information about the objects in an image. This paper presents a comparative analysis of the proposed edge detector with respect to one of the state-of-the-art methods, the Canny edge detector. Our edge detection model involves the supervised optimization of a…
Citare Mărginean, R., Manole, S., Popa, L., Coman, M., Pop, S., Budurea, C., Andreica, A., Dioşan, L., Bálint, Z., Initial validation of an automatic algorithm for whole heart segmentation from cardiac MRI images using atrial volume determination, European congress of radiology (ECR 2020) https://www.myesr.org/congress
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, a…
Despite the promising results obtained by deep learning methods in the field of medical image segmentation, lack of sufficient data always hinders performance to a certain degree. In this work, we explore the feasibility of applying deep learning methods on a pilot dataset. We present a simple and practical approach to perform segmentation in…