These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

142 related articles for article (PubMed ID: 38765316)

  • 1. An Ultralow-Power Real-Time Machine Learning Based fNIRS Motion Artifacts Detection.
    Ercan R; Xia Y; Zhao Y; Loureiro R; Yang S; Zhao H
    IEEE Trans Very Large Scale Integr VLSI Syst; 2024 Apr; 32(4):763-773. PubMed ID: 38765316
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Novel cascade FPGA accelerator for support vector machines classification.
    Papadonikolakis M; Bouganis CS
    IEEE Trans Neural Netw Learn Syst; 2012 Jul; 23(7):1040-52. PubMed ID: 24807131
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Embedded Hardware-Efficient Real-Time Classification With Cascade Support Vector Machines.
    Kyrkou C; Bouganis CS; Theocharides T; Polycarpou MM
    IEEE Trans Neural Netw Learn Syst; 2016 Jan; 27(1):99-112. PubMed ID: 26011869
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Low-Power Hardware Implementation of a Support Vector Machine Training and Classification for Neural Seizure Detection.
    Elhosary H; Zakhari MH; Elgammal MA; Abd El Ghany MA; Salama KN; Mostafa H
    IEEE Trans Biomed Circuits Syst; 2019 Dec; 13(6):1324-1337. PubMed ID: 31613779
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A Model-Based Design Floating-Point Accumulator. Case of Study: FPGA Implementation of a Support Vector Machine Kernel Function.
    Bassoli M; Bianchi V; De Munari I
    Sensors (Basel); 2020 Mar; 20(5):. PubMed ID: 32131395
    [TBL] [Abstract][Full Text] [Related]  

  • 6. SVM classifier on chip for melanoma detection.
    Afifi S; GholamHosseini H; Sinha R
    Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():270-274. PubMed ID: 29059862
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Reconfiguration-based implementation of SVM classifier on FPGA for Classifying Microarray data.
    Hussain HM; Benkrid K; Seker H
    Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():3058-61. PubMed ID: 24110373
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Heterogeneous Hardware Accelerator for Image Classification in Embedded Systems.
    PĂ©rez I; Figueroa M
    Sensors (Basel); 2021 Apr; 21(8):. PubMed ID: 33918668
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Optimized Memory Allocation and Power Minimization for FPGA-Based Image Processing.
    Garcia P; Bhowmik D; Stewart R; Michaelson G; Wallace A
    J Imaging; 2019 Jan; 5(1):. PubMed ID: 34465704
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Toward an Ultralow-Power Onboard Processor for Tongue Drive System.
    Viseh S; Ghovanloo M; Mohsenin T
    IEEE Trans Circuits Syst II Express Briefs; 2015 Feb; 62(2):174-178. PubMed ID: 26185489
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Pure FPGA Implementation of an HOG Based Real-Time Pedestrian Detection System.
    Luo JH; Lin CH
    Sensors (Basel); 2018 Apr; 18(4):. PubMed ID: 29649146
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deep learning-based motion artifact removal in functional near-infrared spectroscopy.
    Gao Y; Chao H; Cavuoto L; Yan P; Kruger U; Norfleet JE; Makled BA; Schwaitzberg S; De S; Intes X
    Neurophotonics; 2022 Oct; 9(4):041406. PubMed ID: 35475257
    [No Abstract]   [Full Text] [Related]  

  • 13. Domain adaptation for robust workload level alignment between sessions and subjects using fNIRS.
    Lyu B; Pham T; Blaney G; Haga Z; Sassaroli A; Fantini S; Aeron S
    J Biomed Opt; 2021 Jan; 26(2):. PubMed ID: 33415849
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Motion Artifacts Correction from Single-Channel EEG and fNIRS Signals Using Novel Wavelet Packet Decomposition in Combination with Canonical Correlation Analysis.
    Hossain MS; Chowdhury MEH; Reaz MBI; Ali SHM; Bakar AAA; Kiranyaz S; Khandakar A; Alhatou M; Habib R; Hossain MM
    Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590859
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Motion artifacts in functional near-infrared spectroscopy: a comparison of motion correction techniques applied to real cognitive data.
    Brigadoi S; Ceccherini L; Cutini S; Scarpa F; Scatturin P; Selb J; Gagnon L; Boas DA; Cooper RJ
    Neuroimage; 2014 Jan; 85 Pt 1(0 1):181-91. PubMed ID: 23639260
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Method for removing motion artifacts from fNIRS data using ICA and an acceleration sensor.
    Hiroyasu T; Nakamura Y; Yokouchi H
    Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():6800-3. PubMed ID: 24111305
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A digital architecture for support vector machines: theory, algorithm, and FPGA implementation.
    Anguita D; Boni A; Ridella S
    IEEE Trans Neural Netw; 2003; 14(5):993-1009. PubMed ID: 18244555
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Hand Motion Detection in fNIRS Neuroimaging Data.
    Abtahi M; Amiri AM; Byrd D; Mankodiya K
    Healthcare (Basel); 2017 Apr; 5(2):. PubMed ID: 28420129
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Hybrid motion artifact detection and correction approach for functional near-infrared spectroscopy measurements.
    Gao L; Wei Y; Wang Y; Wang G; Zhang Q; Zhang J; Chen X; Yan X
    J Biomed Opt; 2022 Feb; 27(2):. PubMed ID: 35212200
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Wavelet-based motion artifact removal for functional near-infrared spectroscopy.
    Molavi B; Dumont GA
    Physiol Meas; 2012 Feb; 33(2):259-70. PubMed ID: 22273765
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.