Publikasi Scopus 2010 s/d 2022

Aprinaldi, Jati G., Gunawan A.A.S., Bowolaksono A., Lestari S.W., Jatmiko W.
57202899749;55490339500;55991217400;57205093224;55980501200;8568432600;
Human Sperm tracking using Particle Swarm Optimization combined with Smoothing Stochastic sampling on low frame rate video
2016
2015 International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015
7438308
7
Faculty of Computer Science, Universitas Indonesia - Depok, Indonesia; Mathematics Department, School of Computer Science, Binus Nusantara University, Indonesia; Faculty of Mathematics and Natural Science Universitas Indonesia, Indonesia; Faculty of Medicine, Universitas Indonesia, Indonesia
Aprinaldi, Faculty of Computer Science, Universitas Indonesia - Depok, Indonesia; Jati, G., Faculty of Computer Science, Universitas Indonesia - Depok, Indonesia; Gunawan, A.A.S., Faculty of Computer Science, Universitas Indonesia - Depok, Indonesia, Mathematics Department, School of Computer Science, Binus Nusantara University, Indonesia; Bowolaksono, A., Faculty of Mathematics and Natural Science Universitas Indonesia, Indonesia; Lestari, S.W., Faculty of Medicine, Universitas Indonesia, Indonesia; Jatmiko, W., Faculty of Computer Science, Universitas Indonesia - Depok, Indonesia
In this paper, we present a technique for visual tracking in the field of Human Sperm motion. Application of sperm cell tracking is mainly important in Intracytoplasmic Sperm Injection (ICSI), a medical procedure that has enabled the In Vitro Fertilization (IVF) of a single sperm which is injected directly into an egg. In this paper, we consider the problem of tracking single object in video sequences of human sperms and a newly developed Smoothing Stochastic Approximate Monte Carlo (SSAMC) based tracker enhanced by Particle Swarm Optimization (PSO). The problem for this research is that the motility or movement of Human Sperm is fast and unpredictable. In addition, each and every sperms have closely similar size and shape. To solve this problem, we used PSO for searching algorithm (finding the best target) in a Search Window, it can reduce the search space in every each consecutive frame. The measurement results of the proposed method are then compared with the manual measurements done by experts. The experiment results were conducted on both open video data and our own video data. Experiment results showed that the proposed method can handle our specific problem in human sperm cell tracking, and give us a better result as compared to our previous tracker, which used geometric transition dynamic model and without any enhancement by PSO. © 2015 IEEE.
Human Sperm Cell Tracking; PSO; Search Window; SSAMC
Problem solving; Social sciences; Stochastic systems; Video recording; Human sperm; Intracytoplasmic sperm injections; Low frame rate video; Manual measurements; Search windows; Searching algorithms; SSAMC; Stochastic sampling; Particle swarm optimization (PSO)
Institute of Electrical and Electronics Engineers Inc.
9,78148E+12
Conference Paper
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