نتائج البحث - "unsupervised machine learning"

المساهمون: University/Department: Universitat Politècnica de Catalunya. Escola Tècnica Superior d'Enginyers de Camins, Canals i Ports de Barcelona

مرشدي الرسالة: Casas Rius, Joan Ramon

المصدر: TDX (Tesis Doctorals en Xarxa)

مصطلحات موضوعية: Structural health monitoring, Bridges damage identification, Vibration parameters, Hilbert–Huang Transform, Empirical mode decomposition, Marginal Hilbert spectrum, Traffic loads, Symbolic data analysis, Unsupervised machine learning, Cluster analysis, Àrees temàtiques de la UPC::Enginyeria civil

وصف الملف: application/pdf

الوصول الحر: http://hdl.handle.net/10803/674150Test

استعراض التسجيلة في TDX

4

رسالة جامعية

Deep learning and unsupervised machine learning for the quantification and interpretation of electrocardiographic signals

المؤلفون: Jiménez-Pérez, Guillermo

المساهمون: University/Department: Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions

مرشدي الرسالة: Camara, Oscar

المصدر: TDX (Tesis Doctorals en Xarxa)

مصطلحات موضوعية: Aprendizaje profundo, Aprendizaje automático no supervisado, Cuantificación, Interpretación, Electrocardiograma, Electrocardiograma intracavitario, Deep learning, Unsupervised machine learning, Quantification, Interpretation, Electrocardiogram, Intracavitary electrocardiogram

وصف الملف: application/pdf

الوصول الحر: http://hdl.handle.net/10803/673555Test

استعراض التسجيلة في TDX

5

دورية أكاديمية

Interpretable unsupervised learning enables accurate clustering with high-throughput imaging flow cytometry.

المؤلفون: Tang, Rui, Zhu, Yuxuan, Guo, Han, Qu, Yunjia, Xie, Pengtao, Lian, Ian, Wang, Yingxiao, Zhang, Zunming, Lo, Yu-Hwa, Chen, Xinyu

المصدر: Scientific Reports. 13(1)

مصطلحات موضوعية: Humans, Unsupervised Machine Learning, Flow Cytometry, Algorithms, Neural Networks, Computer, Cluster Analysis

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/8gv4c3b4Test

View record in eScholarship

6

دورية أكاديمية

A Computational Grounded Approach: A Case Study about Tweets regarding the #Movember Men’s Health Prevention Challenge

المؤلفون: Berriche, Amira, Crié, Dominique, Calciu, Michel

المصدر: Décisions Marketing. 2024, 112(4), p. 79-103.

الإتاحة: https://www.cairn-int.info/article-E_DM_112_0079--a-computational-grounded-approach-a-case-study-about-tweets-regarding-the-movember-mens-health-prevention-challenge.htmTest

View record in Cairn.info

7

دورية أكاديمية

Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality

المؤلفون: Fernando García-García, Dae-Jin Lee, Mónica Nieves-Ermecheo, Olaia Bronte, Pedro Pablo España, José María Quintana, Rosario Menéndez, Antoni Torres, Luis Alberto Ruiz Iturriaga, Isabel Urrutia, COVID-19 & Air Pollution Working Group

المصدر: Pneumonia, Vol 16, Iss 1, Pp 1-16 (2024)

مصطلحات موضوعية: COVID-19, SARS-CoV-2 pneumonia, Phenotypes, Clustering, Unsupervised machine learning, Diseases of the respiratory system, RC705-779

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/2200-6133Test

الوصول الحر: https://doaj.org/article/225bc5553bbc48a581bbb35098060c0bTest

View record in DOAJ

النص الكامل

8

دورية أكاديمية

Unsupervised machine learning for clustering forward head posture, protraction and retraction movement patterns based on craniocervical angle data in individuals with nonspecific neck pain

المؤلفون: Ui-jae Hwang, Oh-yun Kwon, Jun-hee Kim

المصدر: BMC Musculoskeletal Disorders, Vol 25, Iss 1, Pp 1-10 (2024)

مصطلحات موضوعية: Craniocervical alignment, Forward head posture, Neck pain, Unsupervised machine learning, K-means algorithm, Diseases of the musculoskeletal system, RC925-935

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1471-2474Test

الوصول الحر: https://doaj.org/article/ea8aeb6783554a9080daa7e720ba4257Test

View record in DOAJ

النص الكامل

9

دورية أكاديمية

Twenty-four-hour physical activity patterns associated with depressive symptoms: a cross-sectional study using big data-machine learning approach

المؤلفون: Saida Salima Nawrin, Hitoshi Inada, Haruki Momma, Ryoichi Nagatomi

المصدر: BMC Public Health, Vol 24, Iss 1, Pp 1-11 (2024)

مصطلحات موضوعية: Activity pattern, Depressive symptoms, Kernel K-means, Objectively measured physical activity, Time-series clustering, Unsupervised machine learning, Public aspects of medicine, RA1-1270

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1471-2458Test

الوصول الحر: https://doaj.org/article/fb4c309aec23468fb4b79ed97c776e25Test

View record in DOAJ

النص الكامل

10

Automatic document classification in technical logbooks: A comparative study of supervised, weakly supervised and unsupervised machine learning approaches

المؤلفون: Schmidt, Robin Karl

المساهمون: Henriques, Roberto André Pereira, RUN

مصطلحات موضوعية: Document Classification, Technical Language, Supervised Machine Learning, Unsupervised Machine Learning, Semi-Supervised Machine Learning, SDG 9 - Industry, innovation and infrastructure, Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação

وصف الملف: application/pdf

الإتاحة: http://hdl.handle.net/10362/164774Test

View record in RCAAP

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