BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

196 related articles for article (PubMed ID: 35214245)

  • 1. An End-to-End Deep Learning Pipeline for Football Activity Recognition Based on Wearable Acceleration Sensors.
    Cuperman R; Jansen KMB; Ciszewski MG
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214245
    [TBL] [Abstract][Full Text] [Related]  

  • 2. From the Laboratory to the Field: IMU-Based Shot and Pass Detection in Football Training and Game Scenarios Using Deep Learning.
    Stoeve M; Schuldhaus D; Gamp A; Zwick C; Eskofier BM
    Sensors (Basel); 2021 Apr; 21(9):. PubMed ID: 33924985
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Wearable Sensors for Activity Recognition in Ultimate Frisbee Using Convolutional Neural Networks and Transfer Learning.
    Link J; Perst T; Stoeve M; Eskofier BM
    Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408174
    [TBL] [Abstract][Full Text] [Related]  

  • 4. HIT HAR: Human Image Threshing Machine for Human Activity Recognition Using Deep Learning Models.
    Poulose A; Kim JH; Han DS
    Comput Intell Neurosci; 2022; 2022():1808990. PubMed ID: 36248917
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Feature Representation and Data Augmentation for Human Activity Classification Based on Wearable IMU Sensor Data Using a Deep LSTM Neural Network.
    Steven Eyobu O; Han DS
    Sensors (Basel); 2018 Aug; 18(9):. PubMed ID: 30200377
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Human Activity Recognition via Hybrid Deep Learning Based Model.
    Khan IU; Afzal S; Lee JW
    Sensors (Basel); 2022 Jan; 22(1):. PubMed ID: 35009865
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Novel Deep Learning Network for Gait Recognition Using Multimodal Inertial Sensors.
    Shi LF; Liu ZY; Zhou KJ; Shi Y; Jing X
    Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679646
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An Efficient and Lightweight Deep Learning Model for Human Activity Recognition Using Smartphones.
    Ankita ; Rani S; Babbar H; Coleman S; Singh A; Aljahdali HM
    Sensors (Basel); 2021 Jun; 21(11):. PubMed ID: 34199559
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Using Wearable Sensors and a Convolutional Neural Network for Catch Detection in American Football.
    Hollaus B; Stabinger S; Mehrle A; Raschner C
    Sensors (Basel); 2020 Nov; 20(23):. PubMed ID: 33255462
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep CNN-LSTM With Self-Attention Model for Human Activity Recognition Using Wearable Sensor.
    Khatun MA; Yousuf MA; Ahmed S; Uddin MZ; Alyami SA; Al-Ashhab S; Akhdar HF; Khan A; Azad A; Moni MA
    IEEE J Transl Eng Health Med; 2022; 10():2700316. PubMed ID: 35795873
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning-Based Human Activity Real-Time Recognition for Pedestrian Navigation.
    Ye J; Li X; Zhang X; Zhang Q; Chen W
    Sensors (Basel); 2020 Apr; 20(9):. PubMed ID: 32366055
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Effects of sliding window variation in the performance of acceleration-based human activity recognition using deep learning models.
    Jaén-Vargas M; Reyes Leiva KM; Fernandes F; Barroso Gonçalves S; Tavares Silva M; Lopes DS; Serrano Olmedo JJ
    PeerJ Comput Sci; 2022; 8():e1052. PubMed ID: 36091986
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A neural network for the detection of soccer headers from wearable sensor data.
    Kern J; Lober T; Hermsdörfer J; Endo S
    Sci Rep; 2022 Oct; 12(1):18128. PubMed ID: 36307512
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Human activity recognition using wearable sensors, discriminant analysis, and long short-term memory-based neural structured learning.
    Uddin MZ; Soylu A
    Sci Rep; 2021 Aug; 11(1):16455. PubMed ID: 34385552
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep Learning-Based Football Player Detection in Videos.
    Wang T; Li T
    Comput Intell Neurosci; 2022; 2022():3540642. PubMed ID: 35865491
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Feature Fusion of a Deep-Learning Algorithm into Wearable Sensor Devices for Human Activity Recognition.
    Yen CT; Liao JX; Huang YK
    Sensors (Basel); 2021 Dec; 21(24):. PubMed ID: 34960388
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comparison of Data Preprocessing Approaches for Applying Deep Learning to Human Activity Recognition in the Context of Industry 4.0.
    Zheng X; Wang M; Ordieres-Meré J
    Sensors (Basel); 2018 Jul; 18(7):. PubMed ID: 29970873
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep Wavelet Convolutional Neural Networks for Multimodal Human Activity Recognition Using Wearable Inertial Sensors.
    Vuong TH; Doan T; Takasu A
    Sensors (Basel); 2023 Dec; 23(24):. PubMed ID: 38139567
    [TBL] [Abstract][Full Text] [Related]  

  • 19. LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes.
    Mekruksavanich S; Jitpattanakul A
    Sensors (Basel); 2021 Feb; 21(5):. PubMed ID: 33652697
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An improved human activity recognition technique based on convolutional neural network.
    Raj R; Kos A
    Sci Rep; 2023 Dec; 13(1):22581. PubMed ID: 38114574
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.