TY - JOUR N2 - This paper presents an alternative approach to the sequential data classification, based on traditional machine learning algorithms (neural networks, principal component analysis, multivariate Gaussian anomaly detector) and finding the shortest path in a directed acyclic graph, using A* algorithm with a regression-based heuristic. Palm gestures were used as an example of the sequential data and a quadrocopter was the controlled object. The study includes creation of a conceptual model and practical construction of a system using the GPU to ensure the realtime operation. The results present the classification accuracy of chosen gestures and comparison of the computation time between the CPU- and GPU-based solutions. L1 - http://journals.pan.pl/Content/107371/PDF-MASTER/137.pdf L2 - http://journals.pan.pl/Content/107371 PY - 2017 IS - No 2 EP - 265–276 DO - 10.1515/mms-2017-0021 KW - machine learning KW - shortest path KW - sequential data KW - quadrocopter KW - GPU KW - CUDA A1 - Wodziński, Marek A1 - Krzyżanowska, Aleksandra PB - Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation VL - vol. 24 DA - 2017.06.30 T1 - Sequential Classification of Palm Gestures Based on A* Algorithm and MLP Neural Network for Quadrocopter Control SP - 265–276 UR - http://journals.pan.pl/dlibra/publication/edition/107371 T2 - Metrology and Measurement Systems ER -