Výsledky vyhledávání - "stacked convolutional autoencoder"

SCAE—Stacked Convolutional Autoencoder for Fault Diagnosis of a Hydraulic Piston Pump with Limited Data Samples

Autoři: Oybek Eraliev Kwang-Hee Lee Chul-Hee Lee

Zdroj: Sensors, Vol 24, Iss 14, p 4661 (2024)

Témata: fault diagnosis, hydraulic piston pump, stacked convolutional autoencoder, classification, limited data samples, Chemical technology, TP1-1185

Relation: https://www.mdpi.com/1424-8220/24/14/4661; https://doaj.org/toc/1424-8220; https://doaj.org/article/735a294323c5485088429eff4951dccf

Dostupnost: https://doi.org/10.3390/s24144661
https://doaj.org/article/735a294323c5485088429eff4951dccf

Artifact removal from neurophysiological signals: impact on intracranial and arterial pressure monitoring in traumatic brain injury

Autoři: Hakseung Kim Dong-Joo Kim Frederick A. Zeiler a další

Přispěvatelé: Hakseung Kim Dong-Joo Kim Frederick A. Zeiler a další

Zdroj: Journal of Neurosurgery. 132:1952-1960

Témata: 03 medical and health sciences, 0302 clinical medicine, traumatic brain injury, intracranial pressure, convolutional neural network, stacked convolutional autoencoder, cerebral hypoperfusion

Popis souboru: application/octet-stream

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/31075774
https://koreauniv.pure.elsevier.com/en/publications/artifact-removal-from-neurophysiological-signals-impact-on-intrac
https://thejns.org/view/journals/j-neurosurg/132/6/article-p1952.xml
https://www.ncbi.nlm.nih.gov/pubmed/31075774
https://pubmed.ncbi.nlm.nih.gov/31075774/
https://www.repository.cam.ac.uk/handle/1810/291453
https://doi.org/10.3171/2019.2.jns182260
https://doi.org/10.17863/cam.38621

Gait recognition method of coal mine personnel based on Two-Stream neural network

Autoři: Liu Xiaoyang Liu Jinqiang Zheng Haolin

Zdroj: 矿业科学学报, Vol 6, Iss 2, Pp 218-227 (2021)

Témata: underground coal mine personnel, gait recognition, stacked convolutional autoencoder, residual neural network, two-stream neural network, Engineering geology. Rock mechanics. Soil mechanics. Underground construction, TA703-712, Mining engineering. Metallurgy, TN1-997

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2096-2193

Přístupová URL adresa: https://doaj.org/article/b612e7d6f7fd46ffb1f98d612ae18269

A New SCAE-MT Classification Model for Hyperspectral Remote Sensing Images

Autoři: Huayue Chen Ye Chen Qiuyue Wang a další

Zdroj: Sensors, Vol 22, Iss 8881, p 8881 (2022)

Témata: stacked convolutional autoencoder network, transfer learning, feature extraction, small samples, HRSI, Chemical technology, TP1-1185

Relation: https://www.mdpi.com/1424-8220/22/22/8881; https://doaj.org/toc/1424-8220; https://doaj.org/article/6e5c53c528b04a9a934f22282bdde353

Dostupnost: https://doi.org/10.3390/s22228881
https://doaj.org/article/6e5c53c528b04a9a934f22282bdde353

Gait Recognition Method of Underground Coal Mine Personnel Based on Densely Connected Convolution Network and Stacked Convolutional Autoencoder

Autoři: Xiaoyang Liu Jinqiang Liu

Zdroj: Entropy, Vol 22, Iss 695, p 695 (2020)

Témata: underground coal mine personnel, gait recognition, similarity learning, densely connected convolution network, stacked convolutional autoencoder, Two-Stream neural network, Science, Astrophysics, QB460-466, Physics, QC1-999

Relation: https://www.mdpi.com/1099-4300/22/6/695; https://doaj.org/toc/1099-4300; https://doaj.org/article/20cf7dcdd76d4b939451b71332a43bdc

Dostupnost: https://doi.org/10.3390/e22060695
https://doaj.org/article/20cf7dcdd76d4b939451b71332a43bdc

Artifact removal from neurophysiological signals: impact on intracranial and arterial pressure monitoring in traumatic brain injury.

Autoři: Lee, Seung-Bo Kim, Hakseung Kim, Young-Tak a další

Témata: cerebral hypoperfusion, convolutional neural network, intracranial pressure, stacked convolutional autoencoder, traumatic brain injury

Popis souboru: Electronic; application/octet-stream

Relation: https://www.repository.cam.ac.uk/handle/1810/291453

Dostupnost: https://www.repository.cam.ac.uk/handle/1810/291453
https://doi.org/10.17863/CAM.38621

Artifact removal from neurophysiological signals: impact on intracranial and arterial pressure monitoring in traumatic brain injury.

Autoři: Lee, Seung-Bo Kim, Hakseung Kim, Young-Tak a další

Témata: cerebral hypoperfusion, convolutional neural network, intracranial pressure, stacked convolutional autoencoder, traumatic brain injury, Article

URL: https://www.repository.cam.ac.uk/handle/1810/291453

Improved Prediction on Heart Transplant Rejection Using Convolutional Autoencoder and Multiple Instance Learning on Whole-Slide Imaging.

Autoři: Zhu Y Wang MD Tong L a další

Zdroj: ... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics [IEEE EMBS Int Conf Biomed Health Inform] 2019 May; Vol. 2019. Date of Electronic Publication: 2019 Sep 12.

Způsob vydávání: Journal Article

Informace o časopise: Country of Publication: United States NLM ID: 101683138 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2641-3590 (Print) Linking ISSN: 26413590 NLM ISO Abbreviation: IEEE EMBS Int Conf Biomed Health Inform Subsets: PubMed not MEDLINE