Search Results - Földesy, P.

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  1. 1
    Optimization of a Michigan-type silicon microprobe for infrared neural stimulation

    Optimization of a Michigan-type silicon microprobe for infrared neural stimulation by Kiss, M., Földesy, P., Fekete, Z.

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  2. 2
    Microfluidic Particle Sorting System for Environmental Pollution Monitoring Applications

    Microfluidic Particle Sorting System for Environmental Pollution Monitoring Applications by Tóth, E.L., Holczer, E., Földesy, P., Iván, K., Fürjes, P.

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  3. 3
    Pixel-level APS Sensor Integration and Sensitivity Scaling for Vision Based Speed Measurement

    Pixel-level APS Sensor Integration and Sensitivity Scaling for Vision Based Speed Measurement by Németh, M., Zarándy, Á., Földesy, P.

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  4. 4
    A 0.8-μm CMOS two-dimensional programmable mixed-signal focal-plane array processor with on-chip binary imaging and instructions storage

    A 0.8-μm CMOS two-dimensional programmable mixed-signal focal-plane array processor with on-chip binary imaging and instructions storage by Dominguez-Castro, R., Espejo, S., Rodriguez-Vazquez, A., Carmona, R.A., Foldesy, P., Zarandy, A., Szolgay, P., Sziranyi, T., Roska, T.

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  5. 5
    A behavioural modelling technique for visual microprocessor mixed-signal VLSI chips

    A behavioural modelling technique for visual microprocessor mixed-signal VLSI chips by Földesy, P., Rodríguez-Vázquez, A.

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  6. 6
    A behavioural modelling technique for visual microprocessor mixed-signal VLSI chips: CNN Technology

    A behavioural modelling technique for visual microprocessor mixed-signal VLSI chips: CNN Technology by FÖLDESY, P, RODRIGUEZ-VAZQUEZ, A

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  7. 7
    Characterization of silicon field effect transistor sub-THz detectors for imaging systems

    Characterization of silicon field effect transistor sub-THz detectors for imaging systems by Foldesy, P.

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  8. 8
    PDE based histogram modification with embedded morphological processing of the level-sets

    PDE based histogram modification with embedded morphological processing of the level-sets by Cserey, G., Rekeczky, C., Foldesy, P.

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  9. 9
    Image processing library for the Aladdin Visual Computer

    Image processing library for the Aladdin Visual Computer by Szatmari, I., Foldesy, P., Rekeczky, C., Zarandy, A.

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  10. 10
    Moving object tracking on panoramic images

    Moving object tracking on panoramic images by Foldesy, P., Szatmari, I., Zarandy, A.

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  11. 11
    Statistical error modeling of CNN-UM architectures: the binary case

    Statistical error modeling of CNN-UM architectures: the binary case by Foldesy, P.

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  12. 12
    Per-pixel integration time controlled image sensor

    Per-pixel integration time controlled image sensor by Zarandy, A., Foldesy, P., Roska, T.

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  13. 13
    Various implementations of topographic, sensory, cellular wave computers

    Various implementations of topographic, sensory, cellular wave computers by Zarandy, A., Foldesy, M., Szolgay, P., Tokes, S., Rekeczky, C., Roska, T.

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  14. 14
    Test and configuration architecture of a sub-THz CMOS detector array

    Test and configuration architecture of a sub-THz CMOS detector array by Foldesy, P., Gergelyi, D., Fuzy, C., Karolyi, G.

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  15. 15
    Integrated CMOS sub-THz imager array

    Integrated CMOS sub-THz imager array by Foldesy, P., Zarandy, A.

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  16. 16
    Fault-tolerant design of analogic CNN templates and algorithms-Part I: The binary output case

    Fault-tolerant design of analogic CNN templates and algorithms-Part I: The binary output case by Foldesy, P., Kek, L., Zarandy, A., Roska, T., Bartfai, G.

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  17. 17
    Digital Micromirror Device (DMD) projector based test bench for vision chips

    Digital Micromirror Device (DMD) projector based test bench for vision chips by Gergelyi, D., Foldesy, P.

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  18. 18
    Analogic cellular PDE machines

    Analogic cellular PDE machines by Rekeczky, C., Szatmari, I., Foldesy, P., Roska, T.

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  19. 19
    The computational infrastructure of analogic CNN computing. Part I : The CNN-UM chip prototyping system: Bio-inspired processors and cellular neural networks for vision

    The computational infrastructure of analogic CNN computing. Part I : The CNN-UM chip prototyping system: Bio-inspired processors and cellular neural networks for vision by ROSKA, T, ZARANDY, A, ZÖLD, S, FÖLDESY, P, SZOLGAY, P

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  20. 20
    Fault-tolerant design of analogic CNN templates and algorithms. Part I : The binary output case: Bio-inspired processors and cellular neural networks for vision

    Fault-tolerant design of analogic CNN templates and algorithms. Part I : The binary output case: Bio-inspired processors and cellular neural networks for vision by FÖLDESY, P, KEK, L, ZARANDY, A, ROSKA, T, BARTFAI, G

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