BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

251 related articles for article (PubMed ID: 36679624)

  • 1. A Hardware-Friendly High-Precision CNN Pruning Method and Its FPGA Implementation.
    Sui X; Lv Q; Zhi L; Zhu B; Yang Y; Zhang Y; Tan Z
    Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679624
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Hardware-Friendly Low-Bit Power-of-Two Quantization Method for CNNs and Its FPGA Implementation.
    Sui X; Lv Q; Bai Y; Zhu B; Zhi L; Yang Y; Tan Z
    Sensors (Basel); 2022 Sep; 22(17):. PubMed ID: 36081072
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Towards Convolutional Neural Network Acceleration and Compression Based on
    Wei M; Zhao Y; Chen X; Li C; Lu J
    Sensors (Basel); 2022 Jun; 22(11):. PubMed ID: 35684919
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Weak sub-network pruning for strong and efficient neural networks.
    Guo Q; Wu XJ; Kittler J; Feng Z
    Neural Netw; 2021 Dec; 144():614-626. PubMed ID: 34653719
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Adaptive Global Power-of-Two Ternary Quantization Algorithm Based on Unfixed Boundary Thresholds.
    Sui X; Lv Q; Ke C; Li M; Zhuang M; Yu H; Tan Z
    Sensors (Basel); 2023 Dec; 24(1):. PubMed ID: 38203043
    [TBL] [Abstract][Full Text] [Related]  

  • 6. High-Performance Acceleration of 2-D and 3-D CNNs on FPGAs Using Static Block Floating Point.
    Fan H; Liu S; Que Z; Niu X; Luk W
    IEEE Trans Neural Netw Learn Syst; 2023 Aug; 34(8):4473-4487. PubMed ID: 34644253
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Design of Convolutional Neural Network Processor Based on FPGA Resource Multiplexing Architecture.
    Yan F; Zhang Z; Liu Y; Liu J
    Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015728
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Non-Structured DNN Weight Pruning-Is It Beneficial in Any Platform?
    Ma X; Lin S; Ye S; He Z; Zhang L; Yuan G; Tan SH; Li Z; Fan D; Qian X; Lin X; Ma K; Wang Y
    IEEE Trans Neural Netw Learn Syst; 2022 Sep; 33(9):4930-4944. PubMed ID: 33735086
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Acceleration of Deep Neural Network Training Using Field Programmable Gate Arrays.
    Tufa GT; Andargie FA; Bijalwan A
    Comput Intell Neurosci; 2022; 2022():8387364. PubMed ID: 36299439
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Auxiliary Pneumonia Classification Algorithm Based on Pruning Compression.
    Yang CP; Zhu JQ; Yan T; Su QL; Zheng LX
    Comput Math Methods Med; 2022; 2022():8415187. PubMed ID: 35898478
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Designing Deep Learning Hardware Accelerator and Efficiency Evaluation.
    Qi Z; Chen W; Naqvi RA; Siddique K
    Comput Intell Neurosci; 2022; 2022():1291103. PubMed ID: 35875766
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Quantization-Aware NN Layers with High-throughput FPGA Implementation for Edge AI.
    Pistellato M; Bergamasco F; Bigaglia G; Gasparetto A; Albarelli A; Boschetti M; Passerone R
    Sensors (Basel); 2023 May; 23(10):. PubMed ID: 37430583
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs.
    Liu S; Fan H; Ferianc M; Niu X; Shi H; Luk W
    IEEE Trans Neural Netw Learn Syst; 2022 Aug; 33(8):3974-3987. PubMed ID: 33577458
    [TBL] [Abstract][Full Text] [Related]  

  • 14. FPGA-Based Hybrid-Type Implementation of Quantized Neural Networks for Remote Sensing Applications.
    Wei X; Liu W; Chen L; Ma L; Chen H; Zhuang Y
    Sensors (Basel); 2019 Feb; 19(4):. PubMed ID: 30813259
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. A Post-training Quantization Method for the Design of Fixed-Point-Based FPGA/ASIC Hardware Accelerators for LSTM/GRU Algorithms.
    Rapuano E; Pacini T; Fanucci L
    Comput Intell Neurosci; 2022; 2022():9485933. PubMed ID: 35602644
    [TBL] [Abstract][Full Text] [Related]  

  • 17. FPGA-Based Vehicle Detection and Tracking Accelerator.
    Zhai J; Li B; Lv S; Zhou Q
    Sensors (Basel); 2023 Feb; 23(4):. PubMed ID: 36850810
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Hardware Trojan Attacks on the Reconfigurable Interconnections of Field-Programmable Gate Array-Based Convolutional Neural Network Accelerators and a Physically Unclonable Function-Based Countermeasure Detection Technique.
    Hou J; Liu Z; Yang Z; Yang C
    Micromachines (Basel); 2024 Jan; 15(1):. PubMed ID: 38276848
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Evaluation of Deep Neural Network Compression Methods for Edge Devices Using Weighted Score-Based Ranking Scheme.
    Ademola OA; Leier M; Petlenkov E
    Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833610
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks.
    He Y; Dong X; Kang G; Fu Y; Yan C; Yang Y
    IEEE Trans Cybern; 2020 Aug; 50(8):3594-3604. PubMed ID: 31478883
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.