Search Results - "stacked sparse autoencoder"

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  1. 1

    Stacked Sparse Autoencoder Modeling Using the Synergy of Airborne LiDAR and Satellite Optical and SAR Data to Map Forest Above-Ground Biomass by Shao, Zhenfeng, Zhang, Linjing, Wang, Lei

    ISSN: 1939-1404, 2151-1535
    Published: Piscataway IEEE 01.12.2017
    “… However, field data are limited in remote and unmanaged areas. In addition, optical reflectance usually saturates at high-density biomass level and is subject to cloud contaminations…”
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    Journal Article
  2. 2

    A Novel Transfer Learning Approach to Enhance Deep Neural Network Classification of Brain Functional Connectomes by Li, Hailong, Parikh, Nehal A., He, Lili

    ISSN: 1662-453X, 1662-4548, 1662-453X
    Published: Switzerland Frontiers Research Foundation 24.07.2018
    Published in Frontiers in neuroscience (24.07.2018)
    “…Early diagnosis remains a significant challenge for many neurological disorders, especially for rare disorders where studying large cohorts is not possible. A…”
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    Journal Article
  3. 3

    Early prediction of cognitive deficits in very preterm infants using functional connectome data in an artificial neural network framework by He, Lili, Li, Hailong, Holland, Scott K., Yuan, Weihong, Altaye, Mekibib, Parikh, Nehal A.

    ISSN: 2213-1582, 2213-1582
    Published: Netherlands Elsevier Inc 01.01.2018
    Published in NeuroImage clinical (01.01.2018)
    “…Investigation of the brain's functional connectome can improve our understanding of how an individual brain's organizational changes influence cognitive…”
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    Journal Article
  4. 4

    An Optimized Hybrid Soil Texture Classification Model using Stacked Sparse Autoencoder by Prabavathi, R, Chelliah, Balika J

    Published: IEEE 07.12.2023
    “… The dynamic subject of soil classification starts with the model and moves on to explain the classes and, at the end, apply the knowledge gained from the field…”
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    Conference Proceeding
  5. 5

    A Novel Deep Learning Scheme for Motor Imagery EEG Decoding Based on Spatial Representation Fusion by Yang, Jun, Ma, Zhengmin, Wang, Jin, Fu, Yunfa

    ISSN: 2169-3536, 2169-3536
    Published: Piscataway IEEE 2020
    Published in IEEE access (2020)
    “…Motor imagery electroencephalography (MI-EEG), which is an important subfield of active brain-computer interface (BCI) systems, can be applied to help disabled…”
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    Journal Article
  6. 6

    Health Monitoring of Movement Disorder Subject based on Diamond Stacked Sparse Autoencoder Ensemble Model by Tang, Likun, Ma, Jie, Li, Yongming

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 15.03.2023
    Published in arXiv.org (15.03.2023)
    “… To solve this problem, a health monitoring of movement disorder subject based on diamond stacked sparse autoencoder ensemble model (DsaeEM…”
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    Paper
  7. 7

    Deep Learning Based Lithology Classification Using Dual-Frequency Pol-SAR Data by Wang, Wenguang, Ren, Xin, Zhang, Yan, Li, Meng

    ISSN: 2076-3417, 2076-3417
    Published: Basel MDPI AG 01.09.2018
    Published in Applied sciences (01.09.2018)
    “… satisfactory classification accuracy due to high similarity of certain classes. In this paper, a novel Pol-SAR lithology classification method based on a stacked sparse autoencoder (SSAE) is proposed…”
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    Journal Article
  8. 8

    Diagnosis of osteoporosis disease from bone X-ray images with stacked sparse autoencoder and SVM classifier by Nasser, Yassine, El Hassouni, Mohammed, Brahim, Abdelbasset, Toumi, Hechmi, Lespessailles, Eric, Jennane, Rachid

    Published: IEEE 01.05.2017
    “…). However, the diagnosis of osteoporosis confronts two major challenges, the difficulty of distinguishing between osteoporosis and healthy subjects just from the visual inspection of bone X-ray images…”
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    Conference Proceeding
  9. 9

    Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders by Tsinalis, Orestis, Matthews, Paul M., Guo, Yike

    ISSN: 0090-6964, 1573-9686, 1573-9686
    Published: New York Springer US 01.05.2016
    Published in Annals of biomedical engineering (01.05.2016)
    “… We used ensemble learning with an ensemble of stacked sparse autoencoders for classifying the sleep stages…”
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    Journal Article
  10. 10

    Stacked Sparse Autoencoders for EMG-Based Classification of Hand Motions: A Comparative Multi Day Analyses between Surface and Intramuscular EMG by Zia ur Rehman, Muhammad, Gilani, Syed Omer, Waris, Asim, Niazi, Imran Khan, Slabaugh, Gregory, Farina, Dario, Kamavuako, Ernest Nlandu

    ISSN: 2076-3417, 2076-3417
    Published: Basel MDPI AG 01.07.2018
    Published in Applied sciences (01.07.2018)
    “… The aim of this study was to quantify the performance of stacked sparse autoencoders (SSAE), an emerging deep learning technique used to improve myoelectric control and to compare multiday surface electromyography…”
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    Journal Article
  11. 11

    A Hybrid Method of Enhancing Accuracy of Facial Recognition System Using Gabor Filter and Stacked Sparse Autoencoders Deep Neural Network by Jaber, Abdullah Ghanim, Muniyandi, Ravie Chandren, Usman, Opeyemi Lateef, Singh, Harprith Kaur Rajinder

    ISSN: 2076-3417, 2076-3417
    Published: Basel MDPI AG 01.11.2022
    Published in Applied sciences (01.11.2022)
    “…Face recognition has grown in popularity due to the ease with which most recognition systems can find and recognize human faces in images and videos. However,…”
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    Journal Article
  12. 12

    Multiparametric deep learning tissue signatures for a radiological biomarker of breast cancer: Preliminary results by Parekh, Vishwa S., Macura, Katarzyna J., Harvey, Susan C., Kamel, Ihab R., EI‐Khouli, Riham, Bluemke, David A., Jacobs, Michael A.

    ISSN: 0094-2405, 2473-4209, 2473-4209
    Published: United States John Wiley and Sons Inc 01.01.2020
    Published in Medical physics (Lancaster) (01.01.2020)
    “…). The breast tissue signatures are used as inputs in a stacked sparse autoencoder (SSAE) multiparametric deep learning (MPDL…”
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    Journal Article
  13. 13

    Deep learning with leagues championship algorithm based intrusion detection on cybersecurity driven industrial IoT systems by Alotaibi, Saud S., Alghamdi, Turki Ali

    ISSN: 2045-2322, 2045-2322
    Published: London Nature Publishing Group UK 19.08.2025
    Published in Scientific reports (19.08.2025)
    “… However, owing to the constraints of limited resources and computation abilities, IoT networks are subject to different cyber-attacks…”
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    Journal Article
  14. 14

    Hybrid data augmentation method for combined failure recognition in rotating machines by Martins, Dionísio H. C. S. S., de Lima, Amaro A., Pinto, Milena F., Hemerly, Douglas de O., Prego, Thiago de M., e Silva, Fabrício L., Tarrataca, Luís, Monteiro, Ulisses A., Gutiérrez, Ricardo H. R., Haddad, Diego B.

    ISSN: 0956-5515, 1572-8145
    Published: New York Springer US 01.04.2023
    Published in Journal of intelligent manufacturing (01.04.2023)
    “…Rotating machines are frequently subject to a wide range of rough conditions, resulting in mechanical failures and performance degradation…”
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    Journal Article
  15. 15

    MEG Sensor Selection for Neural Speech Decoding by Dash, Debadatta, Wisler, Alan, Ferrari, Paul, Davenport, Elizabeth, Maldjian, Joseph, Wang, Jun

    ISSN: 2169-3536, 2169-3536
    Published: Piscataway IEEE 01.01.2020
    Published in IEEE access (01.01.2020)
    “…Direct decoding of speech from the brain is a faster alternative to current electroencephalography (EEG) speller-based brain-computer interfaces (BCI) in…”
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    Journal Article
  16. 16

    Deep Learning via Stacked Sparse Autoencoders for Automated Voxel-Wise Brain Parcellation Based on Functional Connectivity by Gravelines, Céline

    ISBN: 9798841594475
    Published: ProQuest Dissertations & Theses 01.01.2014
    “… labelled training data, allowing for unsupervised learning. This thesis presents a novel application of stacked sparse autoencoders to the problem of parcellating the brain based on its components’ (voxels…”
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    Dissertation
  17. 17

    Multi-Hierarchical Fusion to Capture the Latent Invariance for Calibration-Free Brain-Computer Interfaces by Yang, Jun, Liu, Lintao, Yu, Huijuan, Ma, Zhengmin, Shen, Tao

    ISSN: 1662-453X, 1662-4548, 1662-453X
    Published: Switzerland Frontiers Media S.A 25.04.2022
    Published in Frontiers in neuroscience (25.04.2022)
    “…Brain-computer interfaces (BCI) based motor imagery (MI) has become a research hotspot for establishing a flexible communication channel for patients with…”
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    Journal Article
  18. 18

    A novel approach for classification of hand movements using surface EMG signals by Zia ur Rehman, Muhammad, Gilani, Syed Omer, Waris, Asim, Niazi, Imran Khan, Kamavuako, Ernest Nlandu

    Published: IEEE 01.12.2017
    “… This paper introduces a novel classifier using Stacked sparse autoencoders (SSAEs) for improved myoelectric control…”
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    Conference Proceeding
  19. 19

    Multiday EMG-Based Classification of Hand Motions with Deep Learning Techniques by Zia ur Rehman, Muhammad, Waris, Asim, Gilani, Syed Omer, Jochumsen, Mads, Niazi, Imran Khan, Jamil, Mohsin, Farina, Dario, Kamavuako, Ernest Nlandu

    ISSN: 1424-8220, 1424-8220
    Published: Switzerland MDPI AG 01.08.2018
    Published in Sensors (Basel, Switzerland) (01.08.2018)
    “… Seven able-bodied subjects performed six active motions (plus rest), and EMG signals were recorded for 15 consecutive days with two sessions per day using the MYO armband…”
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    Journal Article
  20. 20

    Performance of Combined Surface and Intramuscular EMG for Classification of Hand Movements by Rehman, Muhammad Zia Ur, Gillani, Syed Omer, Waris, Asim, Jochumsen, Mads, Niazi, Imran Khan, Kamavuako, Ernest Nlandu

    ISSN: 1557-170X, 2694-0604, 1558-4615, 2694-0604
    Published: United States IEEE 01.07.2018
    “… Six surface and intramuscular channels were recorded concurrently from each subject for seven consecutive days and Stacked sparse autoencoders (SSAE…”
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    Conference Proceeding Journal Article