Výsledky vyhledávání - sparse supervised autoencoder*

Detecting subtle transcriptomic perturbations induced by lncRNAs Knock-Down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network

Autoři: Marin Truchi Caroline Lacoux Cyprien Gille a další

Přispěvatelé: Marin Truchi Caroline Lacoux Cyprien Gille a další

Zdroj: Front Bioinform
Frontiers in Bioinformatics, Vol 4 (2024)

Témata: 0301 basic medicine, single-cell RNA-seq, hypoxia, Bioinformatics, Computer applications to medicine. Medical informatics, 0206 medical engineering, lncRNAs, R858-859.7, CRISPRi, 02 engineering and technology, 3. Good health, [SDV] Life Sciences [q-bio], sparse supervised autoencoder, 03 medical and health sciences, [SDV.BBM] Life Sciences [q-bio]/Biochemistry, Molecular Biology

Popis souboru: application/pdf

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38501112
https://doaj.org/article/961d2c23e9cc4a02a8c14cc9b774b873
https://amu.hal.science/hal-04883524v1
https://amu.hal.science/hal-04883524v1/document
https://doi.org/10.3389/fbinf.2024.1340339
https://hal.science/hal-04795816v1/document
https://hal.science/hal-04795816v1
https://doi.org/10.3389/fbinf.2024.1340339

XAI-DSCSA: explainable-AI-based deep semi-supervised convolutional sparse autoencoder for facial expression recognition

Autoři: M. Mohana P. Subashini George Ghinea

Zdroj: Signal, Image and Video Processing. 19

Témata: autoencoder, semi-supervised learning, convolutional sparse autoencoder, facial expression recognition, feature representation, unsupervised learning

Přístupová URL adresa: https://bura.brunel.ac.uk/handle/2438/31141

Self-Supervised Learning-Based Time Series Classification via Hierarchical Sparse Convolutional Masked-Autoencoder

Autoři: Ting Yu Kele Xu Xu Wang a další

Zdroj: IEEE Open Journal of Signal Processing, Vol 5, Pp 964-975 (2024)

Témata: self-supervised learning, 0202 electrical engineering, electronic engineering, information engineering, Time series classification, time series pre-training, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, TK1-9971

Přístupová URL adresa: https://doaj.org/article/76f3090173e242889fc53ff4c9789e67

Novel semi-supervised sparse stacked autoencoder integrated with local linear embedding for industrial soft sensing

Autoři: Yan-Lin He Yu Jiang Hui-Hui Gao a další

Zdroj: ISA Transactions.

Intelligent evaluation method for identifying favorable shale oil areas based on improved stacked sparse autoencoder

Autoři: Rui Xu Tie Yan Shihui Sun a další

Zdroj: Oil Shale, Vol 42, Iss 1, Pp 79-114 (2025)

Témata: autoencoder, semi-supervised learning, Technology, Q1-390, Science (General), batch normalization, shale oil, favorable area

Detecting subtle transcriptomic perturbations induced by lncRNAs knock-down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network

Autoři: Marin Truchi Caroline Lacoux Cyprien Gille a další

Zdroj: Frontiers in Bioinformatics, Vol 4 (2024)

Témata: single-cell RNA-seq, lncRNAs, hypoxia, CRISPRi, sparse supervised autoencoder, Computer applications to medicine. Medical informatics, R858-859.7

Popis souboru: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fbinf.2024.1340339/full; https://doaj.org/toc/2673-7647

Přístupová URL adresa: https://doaj.org/article/961d2c23e9cc4a02a8c14cc9b774b873

Sparse Autoencoder-guided Supervised Finetuning to Mitigate Unexpected Code-Switching in LLMs

Autoři: Deng, Boyi Wan, Yu Yang, Baosong a další

Témata: FOS: Computer and information sciences, Computation and Language, Computation and Language (cs.CL)

Přístupová URL adresa: http://arxiv.org/abs/2507.14894

Web-S4AE: a semi-supervised stacked sparse autoencoder model for web robot detection

Autoři: Rikhi Ram Jagat Dilip Singh Sisodia Pradeep Singh

Zdroj: Neural Computing and Applications. 35:17883-17898

Self-Supervised Marine Noise Learning with Sparse Autoencoder Network for Generative Target Magnetic Anomaly Detection

Autoři: Shigang Wang Xiangyuan Zhang Yifan Zhao a další

Zdroj: Remote Sensing, Vol 16, Iss 17, p 3263 (2024)

Témata: self-supervised learning (SSL), sparse denoising autoencoder (SDAE), Science, magnetic anomaly detection (MAD), marine noise modeling

Přístupová URL adresa: https://doaj.org/article/9ea907301efc4761bbfcc2d89a02d1ac

Supervised Learning via Unsupervised Sparse Autoencoder

Autoři: Jianran Liu Chan Li Wenyuan Yang

Zdroj: IEEE Access, Vol 6, Pp 73802-73814 (2018)

Témata: sparse autoencoder, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, feature representation, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, supervised learning, dimensionality reduction, TK1-9971

Přístupová URL adresa: https://doaj.org/article/b3d938628d9041e997fd31b0edceac81
http://ieeexplore.ieee.org/document/8558569
https://ieeexplore.ieee.org/document/8558569
https://dblp.uni-trier.de/db/journals/access/access6.html#LiuLY18a

Learning a Sparse Generative Non-Parametric Supervised Autoencoder

Autoři: Michel Barlaud Frederic Guyard

Zdroj: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :3315-3319

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/icassp/icassp2021.html#BarlaudG21

Autoencoders for semi-supervised water level modeling in sewer pipes with sparse labeled data

Autoři: Universitat Politècnica de Catalunya. Doctorat en Automàtica, Robòtica i Visió Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial Barcelona Supercomputing Center a další

Témata: Àrees temàtiques de la UPC::Informàtica::Robòtica, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Supervised learning (Machine learning), Water-pipes, Self-supervised, Semi-supervised, Supervised, Autoencoders and latent space, Sparse data, Data distribution, Water, Aprenentatge supervisat (Aprenentatge automàtic), Aigua -- Canonades, Article

URL: https://hdl.handle.net/2117/363386
https://www.mdpi.com/2073-4441/14/3/333
https://www.mdpi.com/2073-4441/14/3/333

Autoencoders for Semi-Supervised Water Level Modeling in Sewer Pipes with Sparse Labeled Data

Autoři: Ferran Plana Rius Mark P. Philipsen Josep Maria Mirats Tur a další

Přispěvatelé: Ferran Plana Rius Mark P. Philipsen Josep Maria Mirats Tur a další

Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Rius, F P, Philipsen, M P, Tur, J M M, Moeslund, T B, Bahón, C A & Casas, M 2022, 'Autoencoders for Semi-Supervised Water Level Modeling in Sewer Pipes with Sparse Labeled Data', Water (Switzerland), vol. 14, no. 3, 333. https://doi.org/10.3390/w14030333
Water; Volume 14; Issue 3; Pages: 333

Témata: Informàtica::Intel·ligència artificial::Aprenentatge automàtic [Àrees temàtiques de la UPC], Àrees temàtiques de la UPC::Informàtica::Robòtica, Data distribution, Aigua -- Canonades, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, 0211 other engineering and technologies, Sparse data, Water, 02 engineering and technology, self-supervised, semi-supervised, supervised, autoencoders and latent space, sparse data, data distribution, water, Water-pipes, Supervised, Supervised learning (Machine learning), Self-supervised, Aprenentatge supervisat (Aprenentatge automàtic), 0202 electrical engineering, electronic engineering, information engineering, Autoencoders and latent space, Informàtica::Robòtica [Àrees temàtiques de la UPC], Semi-supervised

Popis souboru: application/pdf

Přístupová URL adresa: https://www.mdpi.com/2073-4441/14/3/333/pdf
https://hdl.handle.net/2117/363386
https://doi.org/10.3390/w14030333

A semi-supervised learning framework for gas chimney detection based on sparse autoencoder and TSVM

Autoři: Pengcheng Xu Wenkai Lu Benfeng Wang

Zdroj: Journal of Geophysics and Engineering. 16:52-61

Témata: 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

Přístupová URL adresa: https://academic.oup.com/jge/article/16/1/52/5300202

Handling partially labeled network data: A semi-supervised approach using stacked sparse autoencoder

Autoři: Ons Aouedi Kandaraj Piamrat Dhruvjyoti Bagadthey a další

Přispěvatelé: Ons Aouedi Kandaraj Piamrat Dhruvjyoti Bagadthey a další

Zdroj: Computer Networks. 207:108742

Témata: semi-supervised learning, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], feature extraction, deep learning, 02 engineering and technology, [INFO] Computer Science [cs], partial information, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Machine learning, stacked sparse autoencoder, 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], traffic classification

Popis souboru: application/pdf

Přístupová URL adresa: https://hal.archives-ouvertes.fr/hal-03524935/file/Comnet%20%282%29.pdf
https://hal.science/hal-03524935v1
https://doi.org/10.1016/j.comnet.2021.108742
https://hal.science/hal-03524935v1/document

Sparse Autoencoder Based Semi-Supervised Learning for Phone Classification with Limited Annotations

Autoři: Kumar Dhaka, Akash Salvi, Giampiero

Zdroj: GLU 2017 International Workshop on Grounding Language Understanding. :22-26

Témata: 03 medical and health sciences, Signal Processing, 0202 electrical engineering, electronic engineering, information engineering, Signalbehandling, 02 engineering and technology, 0305 other medical science

Popis souboru: application/pdf

Přístupová URL adresa: http://kth.diva-portal.org/smash/get/diva2:1130230/FULLTEXT01
http://kth.diva-portal.org/smash/record.jsf?pid=diva2:1130230
http://www.diva-portal.org/smash/record.jsf?pid=diva2:1130230
http://kth.diva-portal.org/smash/get/diva2:1130230/FULLTEXT01
http://www.isca-speech.org/archive/GLU_2017/abstracts/GLU2017_paper_5.html
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211654

A Semi-Supervised Approach to Anomaly Detection for Tax Compliance

Autoři: Leo Corman Jason Bono Catherine Acton a další

Témata: autoencoder, sparse data, deep anomaly detection, ensemble, deep learning, semi-supervised

Přístupová URL adresa: https://zenodo.org/records/14009896

Missing Structural and Clinical Features Imputation for Semi-supervised Alzheimer's Disease Classification using Stacked Sparse Autoencoder

Autoři: M. Omair Ahmad Mallappa Kumara Swamy Emimal Jabason

Zdroj: 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS). :1-4

Témata: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/biocas/biocas2018.html#JabasonAS18

Self-supervised Representation Learning Framework for Remote Crop Monitoring Using Sparse Autoencoder

Autoři: J. Anitha S. Immanuel Alex Pandian S. Akila Agnes

Zdroj: Advances in Intelligent Systems and Computing ISBN: 9789811552847

Témata: 2. Zero hunger, 15. Life on land

Přístupová URL adresa: https://rd.springer.com/chapter/10.1007/978-981-15-5285-4_21
https://link.springer.com/chapter/10.1007/978-981-15-5285-4_21

Cervical cancer classification using sparse stacked autoencoder and fuzzy ARTMAP.

Autoři: Liaw, Lawrence Chuin Ming Tan, Shing Chiang Goh, Pey Yun a další

Zdroj: Neural Computing & Applications. Aug2024, Vol. 36 Issue 22, p13895-13913. 19p.

Témata: *TUMOR classification, *SUPERVISED learning, *CERVICAL cancer, *MACHINE learning, *EARLY diagnosis, *DEEP learning