Mouse Tracking Algorithm Based on the Multiple Model Kalman Filter Design and Implementation of Ophthalmological Corrector
Z. Zhang , Visual panel: Virtual mouse keyboard and 3d controller with an ordinary piece of paper. (2001) Proceedings of the Workshop on Perceptive User Interfaces.ACM Press, 2001, pp.1-8.
H.K. Fung, K.H.Wong, A Robust Line Tracking Method Based on a Multiple Model Kalman Filter Model for Mobile Projector Systems (2013), Procedia Technology, 4th International Conference on Electrical Engineering and Informatics (ICEEI), pp. 996-1002
K. Tang, M. Wu. and X. Hu, Multiple model Kalman filtering for mems-imu/gps integrated navigation (2007) In Industrial Electronics and Applications, ICIEA 2nd IEEE Conference, pp. 2062-2066.
M. Isard and A. Blake, Condensation: conditional density propagation for visual tracking (1998) International Journal of Computer Vision 29(1), Kluwer Academic Publishers, pp. 5-28.
S. Mills, T. Pridmore and M. Hills, Tracking in a Hough Space with the Extended Kalman Filter (2003) In proceedings of the British Machine Vision Conference BMVC, September 2003, pp. 173-182.
J. Kubicek, M. Penhaker, I. Bryjova and M. Kodaj, Articular cartilage defect detection based on image segmentation with colour mapping (2014) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8733, pp. 214-222.
J. Kubicek, M. Penhaker, Fuzzy algorithm for segmentation of images in extraction of objects from MRI (2014), Proceedings of the 2014 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014, art. no. 6968264, pp. 1422-1427.
J. Kubicek, M. Penhaker, K. Pavelova, A. Selamat, J. Majernik and R. Hudak, Segmentation of MRI Data to Extract The Blood Vessels Based on Fuzzy Thresholding (2015) In 7th Asian Conference on Inteligent Information and Database Systems ACIIDS. 23th - 25th March, 2015 Bali, Indonesia
D. Angmo, B. Nayak, and V. Gupta, Post-strabismus surgery aqueous misdirection syndrome (2015) BMJ Case Reports, Retinoblastoma: diagnosis and management- the UK perspective (2015) Annals of the Rheumatic Diseases.
J. Kubicek, M. Penhaker, Fuzzy Algorithm for Segmentation of Images in Extraction of Objects from MRI, 2014 International Conference on Advances in Computing, Communications and Informatics (Icacci), pp. 1422-1427, 2014.
Z. Rezaei, A. Selamat, M. S. M. Rahim, and M. R. A. Kadir, Image Segmentation of Coronary Artery Plaque Using Intuitionistic Fuzzy CMeans Algorithm, Proceedings of International Conference on Artificial Life and Robotics (Icarob 2014), pp. 26-31, 2014.
L. Sulik, O. Krejcar, A. Selamat, R. Mashinchi, and K. Kuca, Determining of Blood Artefacts in Endoscopic Images Using a Software Analysis, in Computational Collective Intelligence. vol. 9330, M. Nunez, N. T. Nguyen, D. Camacho, and B. Trawinski, Eds., ed, 2015, pp. 388-397.
J. Blahuta, T. Soukup, and P. Cermak, How to Detect and Analyze Atherosclerotic Plaques in B-MODE Ultrasound Images: A Pilot Study of Reproducibility of Computer Analysis, in Artificial Intelligence: Methodology, Systems, and Applications, Aimsa 2016. vol. 9883, C. Dichev and G. Agre, Eds., ed, 2016, pp. 360-363.
J. Blahuta, T. Soukup, M. Jelinkova, P. Bartova, P. Cermak, R. Herzig, et al., A new program for highly reproducible automatic evaluation of the substantia nigra from transcranial sonographic images, Biomedical Papers-Olomouc, vol. 158, pp. 621-627, 2014
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