BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

373 related articles for article (PubMed ID: 31703174)

  • 1. An FPGA Implementation of Deep Spiking Neural Networks for Low-Power and Fast Classification.
    Ju X; Fang B; Yan R; Xu X; Tang H
    Neural Comput; 2020 Jan; 32(1):182-204. PubMed ID: 31703174
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An FPGA implementation of Bayesian inference with spiking neural networks.
    Li H; Wan B; Fang Y; Li Q; Liu JK; An L
    Front Neurosci; 2023; 17():1291051. PubMed ID: 38249589
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Cost-Efficient High-Speed VLSI Architecture for Spiking Convolutional Neural Network Inference Using Time-Step Binary Spike Maps.
    Zhang L; Yang J; Shi C; Lin Y; He W; Zhou X; Yang X; Liu L; Wu N
    Sensors (Basel); 2021 Sep; 21(18):. PubMed ID: 34577214
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing.
    Kim Y; Panda P
    Neural Netw; 2021 Dec; 144():686-698. PubMed ID: 34662827
    [TBL] [Abstract][Full Text] [Related]  

  • 5. On-Chip Training Spiking Neural Networks Using Approximated Backpropagation With Analog Synaptic Devices.
    Kwon D; Lim S; Bae JH; Lee ST; Kim H; Seo YT; Oh S; Kim J; Yeom K; Park BG; Lee JH
    Front Neurosci; 2020; 14():423. PubMed ID: 32733180
    [TBL] [Abstract][Full Text] [Related]  

  • 6. SSTDP: Supervised Spike Timing Dependent Plasticity for Efficient Spiking Neural Network Training.
    Liu F; Zhao W; Chen Y; Wang Z; Yang T; Jiang L
    Front Neurosci; 2021; 15():756876. PubMed ID: 34803591
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Analyzing and Accelerating the Bottlenecks of Training Deep SNNs With Backpropagation.
    Chen R; Li L
    Neural Comput; 2020 Dec; 32(12):2557-2600. PubMed ID: 32946710
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Training Deep Spiking Neural Networks Using Backpropagation.
    Lee JH; Delbruck T; Pfeiffer M
    Front Neurosci; 2016; 10():508. PubMed ID: 27877107
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Spike-Train Level Direct Feedback Alignment: Sidestepping Backpropagation for On-Chip Training of Spiking Neural Nets.
    Lee J; Zhang R; Zhang W; Liu Y; Li P
    Front Neurosci; 2020; 14():143. PubMed ID: 32231513
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A Scatter-and-Gather Spiking Convolutional Neural Network on a Reconfigurable Neuromorphic Hardware.
    Zou C; Cui X; Kuang Y; Liu K; Wang Y; Wang X; Huang R
    Front Neurosci; 2021; 15():694170. PubMed ID: 34867142
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Boosting Throughput and Efficiency of Hardware Spiking Neural Accelerators Using Time Compression Supporting Multiple Spike Codes.
    Xu C; Zhang W; Liu Y; Li P
    Front Neurosci; 2020; 14():104. PubMed ID: 32140093
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures.
    Lee C; Sarwar SS; Panda P; Srinivasan G; Roy K
    Front Neurosci; 2020; 14():119. PubMed ID: 32180697
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Exploring Optimized Spiking Neural Network Architectures for Classification Tasks on Embedded Platforms.
    Syed T; Kakani V; Cui X; Kim H
    Sensors (Basel); 2021 May; 21(9):. PubMed ID: 34067080
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Pattern Classification Using Quantized Neural Networks for FPGA-Based Low-Power IoT Devices.
    Biswal MR; Delwar TS; Siddique A; Behera P; Choi Y; Ryu JY
    Sensors (Basel); 2022 Nov; 22(22):. PubMed ID: 36433289
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Low-Latency Spiking Neural Networks Using Pre-Charged Membrane Potential and Delayed Evaluation.
    Hwang S; Chang J; Oh MH; Min KK; Jang T; Park K; Yu J; Lee JH; Park BG
    Front Neurosci; 2021; 15():629000. PubMed ID: 33679308
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Supervised Learning in All FeFET-Based Spiking Neural Network: Opportunities and Challenges.
    Dutta S; Schafer C; Gomez J; Ni K; Joshi S; Datta S
    Front Neurosci; 2020; 14():634. PubMed ID: 32670012
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey.
    Dampfhoffer M; Mesquida T; Valentian A; Anghel L
    IEEE Trans Neural Netw Learn Syst; 2023 Apr; PP():. PubMed ID: 37027264
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Effective Plug-Ins for Reducing Inference-Latency of Spiking Convolutional Neural Networks During Inference Phase.
    Chen X; Yuan X; Fu G; Luo Y; Yue T; Yan F; Wang Y; Pan H
    Front Comput Neurosci; 2021; 15():697469. PubMed ID: 34733147
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence.
    Abderrahmane N; Lemaire E; Miramond B
    Neural Netw; 2020 Jan; 121():366-386. PubMed ID: 31593842
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Probabilistic Spike Propagation for Efficient Hardware Implementation of Spiking Neural Networks.
    Nallathambi A; Sen S; Raghunathan A; Chandrachoodan N
    Front Neurosci; 2021; 15():694402. PubMed ID: 34335168
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 19.