Výsledky vyhledávání - deep convolutional autoencoder (ConvAE)

ConvAE-LSTM: Convolutional Autoencoder Long Short-Term Memory Network for Smartphone-Based Human Activity Recognition

Autoři: Dipanwita Thakur Suparna Biswas Edmond S. L. Ho a další

Zdroj: IEEE Access, Vol 10, Pp 4137-4156 (2022)

Témata: Deep Learning, human activity recognition, smartphone sensors, autoencoder, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/9668957/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/b5afcc506cb94c43bf5f07c7e1dd501f

Impartially Validated Multiple Deep-Chain Models to Detect COVID-19 in Chest X-ray Using Latent Space Radiomics

Autoři: Bardia Yousefi Satoru Kawakita Arya Amini a další

Zdroj: Journal of Clinical Medicine, Vol 10, Iss 3100, p 3100 (2021)

Témata: COVID-19 detection, deep convolutional autoencoder (ConvAE), 2D U-Net model, imaging biomarker, deep-learning features, deep latent space radiomics, Medicine

Relation: https://www.mdpi.com/2077-0383/10/14/3100; https://doaj.org/toc/2077-0383; https://doaj.org/article/ed58cfeb1ab04dc9821d3e46241ab42e

Dostupnost: https://doi.org/10.3390/jcm10143100
https://doaj.org/article/ed58cfeb1ab04dc9821d3e46241ab42e

Interpretable regional meteorological feature extraction enhances deep learning for extended 120-h PM2.5 forecasting.

Autoři: Liu, Xinyi Pu, Xueting Lu, Chengwei a další

Zdroj: Journal of Cleaner Production. Dec2024, Vol. 483, pN.PAG-N.PAG. 1p.

Témata: LONG short-term memory, FEATURE extraction, INDEPENDENT variables, AUTOENCODERS, PARTICULATE matter, DEEP learning

Anomaly Detection in Videos Using Optical Flow and Convolutional Autoencoder

Autoři: Elvan Duman Osman Ayhan Erdem

Zdroj: IEEE Access, Vol 7, Pp 183914-183923 (2019)

Témata: Abnormal event detection, convolutional autoencoder, long short-term memory, optical flow, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/8936359/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/db6664ad887d4415b2701096bfaf8f0c

An Application of Deep Learning Technique to Improve Subseasonal to Seasonal Rainfall Forecast over Java Island, Indonesia

Autoři: Adyaksa Budi Raharja Akhmad Faqih Amsari Mudzakir Setiawan

Zdroj: Journal of Natural Resources and Environmental Management, Vol 12, Iss 4 (2022)

Témata: bias correction, convolutional autoencoders, rainfall forecasts, sub-seasonal to seasonal, Environmental sciences, GE1-350

Popis souboru: electronic resource

Relation: https://journal.ipb.ac.id/index.php/jpsl/article/view/39478; https://doaj.org/toc/2086-4639; https://doaj.org/toc/2460-5824

Přístupová URL adresa: https://doaj.org/article/3ee2eda13e0f47a194be2438e8a658c5

Unsupervised anomaly detection for pome fruit quality inspection using X-ray radiography

Autoři: Tempelaere, Astrid He, Jiaqi Van Doorselaer, Leen a další

Zdroj: ISSN:0168-1699 ; ISSN:1872-7107 ; Computers And Electronics In Agriculture, vol. 226, Art.No. ARTN 109364, (109364-109377.

Témata: Science & Technology, Life Sciences & Biomedicine, Technology, Agriculture, Multidisciplinary, Computer Science, Interdisciplinary Applications, Food quality inspection, Deep learning, Anomaly detection, X-ray imaging, Autoencoder, ELEVATED CO2, DISORDERS, FOOD, TOMOGRAPHY, ATTENTION, ALGORITHM, APPLES, 07 Agricultural and Veterinary Sciences, 08 Information and Computing Sciences, 09 Engineering, Agronomy & Agriculture, 30 Agricultural, veterinary and food sciences, 40 Engineering, 46 Information and computing sciences

Popis souboru: application/msword

Relation: https://lirias.kuleuven.be/handle/20.500.12942/748827; https://doi.org/10.1016/j.compag.2024.109364

Dostupnost: https://lirias.kuleuven.be/handle/20.500.12942/748827
https://hdl.handle.net/20.500.12942/748827
https://lirias.kuleuven.be/retrieve/166fe19e-6c63-4a2e-b1be-4ad85a4dfe4b
https://doi.org/10.1016/j.compag.2024.109364

Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights

Autoři: Wu, Shih-Lun Tung, Hsiao-Yen Hsu, Yu-Lun

Témata: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/2011.11378

Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale

Autoři: Landi, Isotta Glicksberg, Benjamin S. Lee, Hao-Chih a další

Témata: Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2003.06516

Impartially Validated Multiple Deep-Chain Models to Detect COVID-19 in Chest X-ray Using Latent Space Radiomics.

Autoři: Yousefi, Bardia Kawakita, Satoru Amini, Arya a další

Zdroj: Journal of Clinical Medicine; Jul2021, Vol. 10 Issue 14, p3100-3100, 1p

Témata: RADIOMICS, COVID-19, COMPUTER-aided diagnosis, COVID-19 pandemic, PRINCIPAL components analysis

An end-to-end intrusion detection system with IoT dataset using deep learning with unsupervised feature extraction.

Autoři: Kunang, Yesi Novaria Nurmaini, Siti Stiawan, Deris a další

Zdroj: International Journal of Information Security; Jun2024, Vol. 23 Issue 3, p1619-1648, 30p

Témata: DEEP learning, FEATURE extraction, MACHINE learning, INTERNET of things

Predicting the influence of extreme temperatures on grain production in the Middle-Lower Yangtze Plains using a spatially-aware deep learning model.

Autoři: Mu, Zijun Xia, Junfei

Zdroj: PeerJ; Oct2024, p1-26, 26p

Deep Crowd Anomaly Detection by Fusing Reconstruction and Prediction Networks.

Autoři: Sharif, Md. Haidar Jiao, Lei Omlin, Christian W.

Zdroj: Electronics (2079-9292); Apr2023, Vol. 12 Issue 7, p1517, 41p

Témata: ANOMALY detection (Computer security), ARTIFICIAL neural networks, COMPUTER vision, FEATURE extraction, DEEP learning

Deep Crowd Anomaly Detection by Fusing Reconstruction and Prediction Networks

Autoři: Sharif, Md Haidar Lei, Jiao Omlin, Christian Walter Peter

Zdroj: 12 ; Electronics ; 7 ; 1517

Témata: VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550

Popis souboru: application/pdf

Relation: Norges forskningsråd: 320783; Sharif, M. H., Lei, J. & Omlin, C. W. P. (2023). Deep Crowd Anomaly Detection by Fusing Reconstruction and Prediction Networks. Electronics, 12 (7), Article 1517.; https://hdl.handle.net/11250/3127027; https://doi.org/10.3390/electronics12071517; cristin:2148393

Dostupnost: https://hdl.handle.net/11250/3127027
https://doi.org/10.3390/electronics12071517

Deep representation learning of electronic health records to unlock patient stratification at scale

Autoři: Isotta Landi Benjamin S. Glicksberg Hao-Chih Lee a další

Zdroj: npj Digital Medicine, Vol 3, Iss 1, Pp 1-11 (2020)

Témata: Computer applications to medicine. Medical informatics, R858-859.7

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2398-6352

Přístupová URL adresa: https://doaj.org/article/a3c812cf99b140a5b237ea6ab049acf1

ConvAE-LSTM: convolutional autoencoder long short-term memory network for smartphone-based human activity recognition

Autoři: Thakur, Dipanwita Biswas, Suparna Ho, Edmond S. L. a další

Popis souboru: text

Relation: https://eprints.gla.ac.uk/276355/1/276355.pdf; Thakur, D., Biswas, S., Ho, E. S. L. and Chattopadhyay, S. (2022) ConvAE-LSTM: convolutional autoencoder long short-term memory network for smartphone-based human activity recognition. IEEE Access , 10, pp. 4137-4156. (doi:10.1109/ACCESS.2022.3140373 )

Dostupnost: https://eprints.gla.ac.uk/276355/
https://eprints.gla.ac.uk/276355/1/276355.pdf

Automated adversarial detection in mobile apps using API calls and permissions

Autoři: Somanathan Pillai, Sanjaikanth E Vadakkethil Vallabhaneni, Rohith Vaddadi, Srinivas A a další

Zdroj: Indonesian Journal of Electrical Engineering and Computer Science; Vol 37, No 3: March 2025; 1672-1681 ; 2502-4760 ; 2502-4752 ; 10.11591/ijeecs.v37.i3

Témata: Android mobile apps, Application programming interface calls, Deep learning, Permission, SD_ConvAE model, Third-party attacks

Popis souboru: application/pdf

Relation: https://ijeecs.iaescore.com/index.php/IJEECS/article/view/37336/19014; https://ijeecs.iaescore.com/index.php/IJEECS/article/view/37336

Dostupnost: https://ijeecs.iaescore.com/index.php/IJEECS/article/view/37336
https://doi.org/10.11591/ijeecs.v37.i3.pp1672-1681

New channel autoencoder and deep-learning based channel state information feedback schemes for massive MIMO systems ; Massive MIMO 시스템을 위한 새로운 채널 오토인코더 및 딥러닝 기반 채널 상태 정보 피드백 방안

Autoři: Ji, Dong Jin Cho, Dongho 조동호 a další

Přispěvatelé: Ji, Dong Jin Cho, Dongho 조동호 a další

Témata: Machine learning for communications▼aDeep learning▼aMIMO▼aChannel feedback▼aChannel autoencoder, 통신을 위한 기계 학습▼a딥 러닝▼a마이모▼a채널 피드백▼a채널 오토인코더

Relation: 956687; http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=956687&flag=dissertation; http://hdl.handle.net/10203/295695; 325007; 1130

Dostupnost: http://hdl.handle.net/10203/295695
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=956687&flag=dissertation

Anomaly detection for multivariate times series through the multi-scale convolutional recurrent variational autoencoder.

Autoři: Xie, Tianming Xu, Qifa Jiang, Cuixia

Zdroj: Expert Systems with Applications. Nov2023, Vol. 231, pN.PAG-N.PAG. 1p.

Témata: *ANOMALY detection (Computer security), *TIME series analysis, *LATENT variables, *DEEP learning, *RECURRENT neural networks

Watershed groundwater level multistep ahead forecasts by fusing convolutional-based autoencoder and LSTM models.

Autoři: Kow, Pu-Yun Liou, Jia-Yi Sun, Wei a další

Zdroj: Journal of Environmental Management. Feb2024, Vol. 351, pN.PAG-N.PAG. 1p.

Témata: *WATER table, *DEEP learning, *WATER management, *CONVOLUTIONAL neural networks, *GROUNDWATER management, *FORECASTING, *WELLS

Geografický termín: TAIWAN

An image compression approach for efficient pneumonia recognition.

Autoři: Nefoussi, Sabrina Amamra, Abdenour Amarouche, Idir Amine

Zdroj: Imaging Science Journal; May2024, Vol. 72 Issue 3, p304-317, 14p