T
T. Baidyk
Researcher at National Autonomous University of Mexico
Publications - 28
Citations - 676
T. Baidyk is an academic researcher from National Autonomous University of Mexico. The author has contributed to research in topics: MNIST database & Artificial neural network. The author has an hindex of 13, co-authored 28 publications receiving 618 citations.
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Journal ArticleDOI
Improved method of handwritten digit recognition tested on MNIST database
Ernst Kussul,T. Baidyk +1 more
TL;DR: A novel neural classifier LImited Receptive Area (LIRA) for the image recognition that contains three neuron layers: sensor, associative and output layers and shows sufficiently good results in task of the pin–hole position estimation.
Journal ArticleDOI
Development of micromachine tool prototypes for microfactories
Ernst Kussul,T. Baidyk,Leopoldo Ruiz-Huerta,Alberto Caballero-Ruiz,Graciela Velasco,L. Kasatkina +5 more
TL;DR: In this paper, an alternative technology of micromechanical device production is proposed based on micromachine tools (MMT) and microassembly devices, which can be produced as sequential generations of microequipment.
Journal ArticleDOI
Micromechanical engineering: a basis for the low-cost manufacturing of mechanical microdevices using microequipment
TL;DR: In this article, a series of equipment generations with gradually decreasing dimensions are proposed to reduce power consumption and floor area occupied, which in turn will reduce the cost of micro-equipment.
Journal ArticleDOI
Flat image recognition in the process of microdevice assembly
T. Baidyk,Ernst Kussul,Oleksandr Makeyev,Alberto Caballero,L. Ruiz,Gerardo Carrera,Graciela Velasco +6 more
TL;DR: An image recognition system for use in the assembly of microdevices gives an increase in theassembly process precision and will be used for assembly of microring-based filters.
Proceedings ArticleDOI
Rosenblatt perceptrons for handwritten digit recognition
TL;DR: It was shown that a large scale Rosenblatt perceptron is comparable with the best classifiers checked on MNIST database, and the influence of the critical parameter N, the number of neurons N in the associative neuron layer, is investigated.