Výsledky vyhľadávania - "Layered sparse autoencoder"

Hybrid Greylag Goose deep learning with layered sparse network for women nutrition recommendation during menstrual cycle

Autori: E. Logapriya Surendran Rajendran Mohammad Zakariah

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-22 (2025)

Predmety: Menstrual cycle, Pre-processing, Layered sparse autoencoder, Deep learning, Greylag Goose optimization, Bidirectional gated recurrent unit, Medicine, Science

Popis súboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Prístupová URL adresa: https://doaj.org/article/1fdc03bab0db474c8ebe8a2b866bf2e9

Hybrid Greylag Goose deep learning with layered sparse network for women nutrition recommendation during menstrual cycle.

Autori: Logapriya, E. Rajendran, Surendran Zakariah, Mohammad

Zdroj: Scientific Reports; 2/18/2025, Vol. 15 Issue 1, p1-22, 22p

Predmety: OPTIMIZATION algorithms, DEEP learning, AUTOENCODERS, NUTRITIONAL requirements, FEATURE extraction, MENSTRUATION, MENSTRUAL cycle

A transfer learning-based fault diagnosis method for rolling bearings with variable operating conditions.

Autori: Song, Cunli Yuan, Xiaomeng

Zdroj: Applied Intelligence; Sep2025, Vol. 55 Issue 14, p1-13, 13p

Supervised Learning via Unsupervised Sparse Autoencoder

Autori: Jianran Liu Chan Li Wenyuan Yang

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

Predmety: Machine learning, dimensionality reduction, sparse autoencoder, supervised learning, feature representation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis súboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/8558569/; https://doaj.org/toc/2169-3536

Prístupová URL adresa: https://doaj.org/article/b3d938628d9041e997fd31b0edceac81

An improved approach of high graded glioma segmentation using sparse autoencoder and fuzzy c-means clustering from multi-modal MR images.

Autori: Bhattacharya, Debanjali Sinha, Neelam

Zdroj: Proceedings of SPIE; 1/6/2018, Vol. 10578, p1-9, 9p

Robust approach for AMC in frequency selective fading scenarios using unsupervised sparse‐autoencoder‐based deep neural network.

Autori: Shah, Maqsood Hussain Dang, Xiaoyu

Zdroj: IET Communications (Wiley-Blackwell); Mar2019, Vol. 13 Issue 4, p423-432, 10p

Predmety: ARTIFICIAL neural networks, ARTIFICIAL intelligence, DEEP learning, ORDER statistics, SIGNAL classification

Off-the-shelf CNN features for 3D object retrieval.

Autori: Wang, Dong Wang, Bin Zhao, Sicheng a ďalší

Zdroj: Multimedia Tools & Applications; Aug2018, Vol. 77 Issue 15, p19833-19849, 17p

Predmety: THREE-dimensional display systems, DEEP learning, MULTIGRAPH, IMAGE processing, ENCODING

Exploring a Mixed Representation for Encoding Temporal Coherence.

Autori: Parkinson, Jon Sandouk, Ubai Chen, Ke

Zdroj: Machine Learning & Knowledge Discovery in Databases: European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II; 2016, p347-360, 14p

Deep net architectures for visual-based clothing image recognition on large database.

Autori: Chen, Ju-Chin Liu, Chao-Feng

Zdroj: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Jun2017, Vol. 21 Issue 11, p2923-2939, 17p

Predmety: BIG data, DEEP learning, NEURAL circuitry, IMAGE recognition (Computer vision), CLOTHING & dress

Fuzzy Rule Reduction using Sparse Auto-Encoders.

Autori: Sevakula, Rahul K. Verma, Nishchal K.

Zdroj: 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE); 2015, p1-7, 7p

Using the Deformable Part Model with Autoencoded Feature Descriptors for Object Detection

Autori: Hyunghoon Cho David Wu The Pennsylvania State University CiteSeerX Archives

Prispievatelia: Hyunghoon Cho David Wu The Pennsylvania State University CiteSeerX Archives

Zdroj: http://cs229.stanford.edu/proj2010/ChoWu-AutoencoderFeatureDescriptors.pdf.

Popis súboru: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.374.9070

Dostupnosť: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.374.9070
http://cs229.stanford.edu/proj2010/ChoWu-AutoencoderFeatureDescriptors.pdf

Sensor and Component Fault Detection and Diagnosis for Hydraulic Machinery Integrating LSTM Autoencoder Detector and Diagnostic Classifiers.

Autori: Mallak, Ahlam Fathi, Madjid

Zdroj: Sensors (14248220); Jan2021, Vol. 21 Issue 2, p433, 1p

Predmety: FAULT diagnosis, SUPERVISED learning, BEARINGS (Machinery), HYDRAULIC machinery, CONDENSED matter, DETECTORS, MACHINERY safety

Comparing biological information contained in mRNA and non-coding RNAs for classification of lung cancer patients.

Autori: Smolander, Johannes Stupnikov, Alexey Glazko, Galina a ďalší

Zdroj: BMC Cancer; 12/3/2019, Vol. 19 Issue 1, pN.PAG-N.PAG, 1p, 4 Charts, 5 Graphs

Predmety: NON-coding RNA, TUMOR classification, LUNG cancer, NON-small-cell lung carcinoma, MESSENGER RNA, ADENOCARCINOMA, RNA sequencing, DEEP learning

Fourth Congress on Intelligent Systems

Autori: Sandeep Kumar K. Balachandran Joong Hoon Kim a ďalší

Typ zdroja: eBook.

Predmet: Computational intelligence, Artificial intelligence, Robotics

Kategórie: COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Engineering (General), TECHNOLOGY & ENGINEERING / Robotics

Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2016, Riva Del Garda, Italy, September 19-23, 2016, Proceedings, Part II

Autori: Paolo Frasconi Niels Landwehr Giuseppe Manco a ďalší

Typ zdroja: eBook.

Predmet: Data mining, Artificial intelligence, Pattern recognition systems, Information storage and retrieval systems, Database management, Application software

Kategórie: COMPUTERS / Data Science / Data Analytics, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Business & Productivity Software / General, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Database Administration & Management, COMPUTERS / System Administration / Storage & Retrieval, MATHEMATICS / Probability & Statistics / General