Výsledky vyhledávání - Convolutional autoencoder network

Spatially Aware Fusion in 3D Convolutional Autoencoders for Video Anomaly Detection

Autoři: Niaz, Asim Ul Amin, Sareer Soomro, Shafiullah a další

Zdroj: IEEE Access. 12:104770-104784

Témata: Videos, Anomaly detection, Surveillance, Feature extraction, Predictive models, Pedestrians, Optical flow, autoencoders, computer vision, intelligent surveillance systems, three-dimensional convolutional neural network (3DCNN), video-based abnormal event detection, Computer Science, Datavetenskap

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-132046
https://doi.org/10.1109/ACCESS.2024.3435144

Image Dehazing Using a Convolutional Autoencoder Network with Integrated Convolutional Block Attention

Autoři: Rastegar, Homayoun Khotanlou, Hassan

Convolutional autoencoder network lithology recognition based on scratch tests

Autoři: Suling Wang Zhihui Ren Kangxing Dong a další

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-16 (2025)

Témata: Continental shale, Lithology recognition, Scratch tests, Recognition size, CAE network, Medicine, Science

Popis souboru: electronic resource

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

Přístupová URL adresa: https://doaj.org/article/f7f862af682241f488ef0ed868100a5f

Cascaded hybrid convolutional autoencoder network for spectral-spatial nonlinear hyperspectral unmixing

Autoři: Jinbin Wu Jiankang Zhao Haihui Long

Zdroj: International Journal of Remote Sensing. 45:9267-9286

A targeted one dimensional fully convolutional autoencoder network for intelligent compression of magnetic flux leakage data

Autoři: Wenbo Xuan Pengchao Chen Rui Li a další

Zdroj: Sci Rep
Scientific Reports, Vol 15, Iss 1, Pp 1-13 (2025)

Témata: Science, Medicine, Article

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40181135
https://doaj.org/article/843300ddd0b346febc0e8d2382397ead

Looseness Identification of Track Fasteners Based on Ultra-Weak FBG Sensing Technology and Convolutional Autoencoder Network

Autoři: Li, Sheng Jin, Liang Jiang, Jinpeng a další

Zdroj: Sensors. 22(15)

Témata: Data Management and Data Science, Civil Engineering, Information and Computing Sciences, Engineering, Clinical Research, Railroads, Technology, feature identification, track fastener looseness, distributed vibration, convolutional autoencoder network, pseudo-Hilbert scan, ultra-weak fiber optic Bragg grating, Analytical Chemistry, Environmental Science and Management, Ecology, Distributed Computing, Electrical and Electronic Engineering, Electrical engineering, Electronics, sensors and digital hardware, Environmental management, Distributed computing and systems software

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/4jq321md
https://escholarship.org/content/qt4jq321md/qt4jq321md.pdf

Speech Enhancement using Convolutional Autoencoder Network

Autoři: Subhadeep Sengupta Pranav Rihal Allwin D’Souza

Zdroj: INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT. :1-11

A Novel Spatiotemporal Enhanced Convolutional Autoencoder Network for Unsupervised Health Indicator Construction

Autoři: Shuaiyong Li Chao Zhang Xuyuntao Zhang

Zdroj: IEEE Transactions on Instrumentation and Measurement. 73:1-10

CAEM-GBDT: a cancer subtype identifying method using multi-omics data and convolutional autoencoder network

Autoři: Jiquan Shen Xuanhui Guo Hanwen Bai a další

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

Témata: 0301 basic medicine, 03 medical and health sciences, Bioinformatics, Computer applications to medicine. Medical informatics, 0206 medical engineering, R858-859.7, convolutional block attention module, cancer subtype, 02 engineering and technology, cancer subtype identification, multi-omics, convolutional autoencode, 3. Good health

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39077754
https://doaj.org/article/4f014307b12741179c935d5f6d0a9626

Spatiotemporal Image-Based Flight Trajectory Clustering Model with Deep Convolutional Autoencoder Network

Autoři: Ye Liu Kam K. H. Ng Nana Chu a další

Zdroj: Journal of Aerospace Information Systems. 20:575-587

Témata: 0502 economics and business, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Domestic Activity Clustering from Audio via Depthwise Separable Convolutional Autoencoder Network

Autoři: Li, Yanxiong Cao, Wenchang Drossos, Konstantinos a další

Přispěvatelé: Li, Yanxiong Cao, Wenchang Drossos, Konstantinos a další

Zdroj: 2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP). :1-6

Témata: FOS: Computer and information sciences, Sound (cs.SD), Audio and Speech Processing (eess.AS), FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 113 Computer and information sciences, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing

Popis souboru: fulltext

Přístupová URL adresa: http://arxiv.org/abs/2208.02406
https://trepo.tuni.fi/handle/10024/150616

CAE SynthImgGen: Revolutionizing cancer diagnosis with convolutional autoencoder-based synthetic image generation.

Autoři: Hangaragi, Shivalila Neelima, N. Venugopal, Vivek a další

Zdroj: Alexandria Engineering Journal. Mar2025, Vol. 115, p343-354. 12p.

Témata: Convolutional neural networks, Machine learning, Computer-assisted image analysis (Medicine), Autoencoder, Databases, Deep learning

Predicting Wave Propagation for Varying Bathymetry Using Conditional Convolutional Autoencoder Network

Autoři: Indu Kant Deo Akash Vankateshwaran Rajeev Jaiman

Zdroj: Volume 6: Polar and Arctic Sciences and Technology; CFD, FSI, and AI.

Témata: 14. Life underwater

Reconstruction of pile-up events using a one-dimensional convolutional autoencoder for the NEDA detector array

Autoři: Deltoro, J. M. Jaworski, G. Goasduff, A. a další

Zdroj: Nuclear Science and Techniques. 36(2)

Témata: 1D-CAE, Autoencoder, CAE, Convolutional neural network (CNN), Neutron detector, Neutron-gamma discrimination (NGD), Machine learning, Pulse shape discrimination, Pile-up pulse

Popis souboru: print

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-548603

Inpainting non-anatomical objects in brain imaging using enhanced deep convolutional autoencoder network

Autoři: Puranam Revanth Kumar B Shilpa Rajesh Kumar Jha a další

Zdroj: Sādhanā. 49

Sparsity Constrained Convolutional Autoencoder Network for Hyperspectral Image Unmixing

Autoři: Tao Huang Zhengang Zhao Yuchen Liang a další

Zdroj: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. :3317-3320

Témata: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://ieeexplore.ieee.org/document/9553239
https://dblp.uni-trier.de/db/conf/igarss/igarss2021.html#ZhaoWLHXY21

Mineral Prospectivity Prediction by Integration of Convolutional Autoencoder Network and Random Forest

Autoři: Na Yang Zhenkai Zhang Jianhua Yang a další

Zdroj: Natural Resources Research. 31:1103-1119

Témata: 0101 mathematics, 01 natural sciences, 0105 earth and related environmental sciences

Simulating clinical features on chest radiographs for medical image exploration and CNN explainability using a style-based generative adversarial autoencoder.

Autoři: Hasenstab, Kyle Hahn, Lewis Chao, Nick a další

Zdroj: Scientific Reports. 14(1)

Témata: Autoencoder, Chest radiographs, Convolutional neural network, Explainable artificial intelligence, Generative adversarial network, Humans, Radiography, Thoracic, Neural Networks, Computer, Male, Female, Natriuretic Peptide, Brain, Middle Aged, Aged, Peptide Fragments, Heart Failure, Image Processing, Computer-Assisted

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/1tq0z60t
https://escholarship.org/content/qt1tq0z60t/qt1tq0z60t.pdf

Vector Quantized Convolutional Autoencoder Network for LDCT Image Reconstruction with Hybrid Loss

Autoři: Shalini Ramanathan Mohan Ramasundaram

Zdroj: SN Computer Science. 5

Convolutional autoencoder network lithology recognition based on scratch tests.

Autoři: Wang, Suling Ren, Zhihui Dong, Kangxing a další

Zdroj: Scientific Reports; 8/19/2025, Vol. 15 Issue 1, p1-16, 16p

Témata: SHALE gas reservoirs, ARTIFICIAL neural networks, GEOLOGICAL modeling, PETROLOGY, MECHANICAL behavior of materials, HARDNESS testing

Geografický termín: CHINA, JILIN (Jilin Sheng, China)