S
Sandor Szenasi
Researcher at Óbuda University
Publications - 93
Citations - 372
Sandor Szenasi is an academic researcher from Óbuda University. The author has contributed to research in topics: Computer science & Heat transfer coefficient. The author has an hindex of 10, co-authored 77 publications receiving 274 citations. Previous affiliations of Sandor Szenasi include Selye János University.
Papers
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Implementation of a Distributed Genetic Algorithm for Parameter Optimization in a Cell Nuclei Detection Project
Sandor Szenasi,Zoltan Vamossy +1 more
TL;DR: The paper summarizes the development of an evolution-based algorithm that was used to successfully determine a set of parameters that could be used to achieve significantly better accuracy than the already existing parameters.
Proceedings ArticleDOI
Parallel biomedical image processing with GPGPUs in cancer research
Attila Remenyi,Sandor Szenasi,I Bándi,Zoltan Vamossy,Gábor Valcz,Pal Bogdanov,Szabolcs Sergyan,Miklos Kozlovszky +7 more
TL;DR: This work focuses on how to achieve better performance with coalesced global memory access when working with three-channel RGB tissue images, and how to use the on-die shared memory efficiently.
Proceedings ArticleDOI
Occlusion Handling in Generic Object Detection: A Review
TL;DR: In this paper, the authors address the challenges in occlusion handling in generic object detection in both outdoor and indoor scenes, then refer to the recent works that have been carried out to overcome these challenges.
Proceedings ArticleDOI
Configuring genetic algorithm to solve the inverse heat conduction problem
Sandor Szenasi,Imre Felde +1 more
TL;DR: In this article, the results of several experimental tests to find the appropriate attributes of a genetic algorithm based approach to quickly and reliably solve the inverse heat conduction problem are presented. But, the main mechanisms of these approaches are well-known, the practical implementations raise several questions about the free parameters (population size, elitism, mutation probability/range, etc.).
Proceedings ArticleDOI
Evaluation and comparison of cell nuclei detection algorithms
TL;DR: The purpose of the article is to develop a generally usable measurement number that is based on the “gold standard” tests used in the field of medicine and that can be used to perform an evaluation using any of image segmentation algorithms.