Suchergebnisse - Cascade Autoencoder

Blade performance prediction model coupled autoencoder with multi-source data fusion strategy

Autoren: Ruoyu Chen Ziliang Li Huafeng Xu et al.

Quelle: Engineering Applications of Computational Fluid Mechanics, Vol 19, Iss 1 (2025)

Schlagwörter: Small-sample deep learning, multi-source data fusion, blade loss prediction, convolutional autoencoder, compressor cascade, Engineering (General). Civil engineering (General), TA1-2040

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1994-2060; https://doaj.org/toc/1997-003X

Zugangs-URL: https://doaj.org/article/2362ca3016fc4bdfa407ed38dd032f61

Spatial-Temporal Cascade Autoencoder for Video Anomaly Detection in Crowded Scenes

Autoren: Nanjun Li Faliang Chang Chunsheng Liu

Quelle: IEEE Transactions on Multimedia. 23:203-215

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://ieeexplore.ieee.org/abstract/document/9055131
https://ieeexplore.ieee.org/document/9055131
https://dblp.uni-trier.de/db/journals/tmm/tmm23.html#LiCL21
https://doi.org/10.1109/TMM.2020.2984093

Gravitational wave isolation with autoencoder neural network cascade.

Autoren: Sengupta, Mayank¹ (AUTHOR) mayanksengupta@acm.org

Quelle: Neural Computing & Applications. May2024, Vol. 36 Issue 13, p6993-7006. 14p.

Schlagwörter: *GRAVITATIONAL waves, *GRAVITATIONAL wave detectors, *CASCADE connections, *GRAVITATIONAL wave astronomy, *GRAVITATIONAL fields, *BINARY black holes, *GRAPHICS processing units

Prediction of miRNA–Disease Associations by Cascade Forest Model Based on Stacked Autoencoder

Autoren: Xiang Hu Zhixiang Yin Zhiliang Zeng et al.

Quelle: Molecules, Vol 28, Iss 13, p 5013 (2023)

Schlagwörter: miRNA–disease association, multi-source information, stacked autoencoder, cascade forest, Organic chemistry, QD241-441

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1420-3049/28/13/5013; https://doaj.org/toc/1420-3049

Zugangs-URL: https://doaj.org/article/01a5bdab91a149018b0b974a5a968814

A Variational Autoencoder Cascade Generative Adversarial Network for Scalable 3D Object Generation and Reconstruction

Autoren: Min-Su Yu Tae-Won Jung Dai-Yeol Yun et al.

Quelle: Sensors, Vol 24, Iss 3, p 751 (2024)

Schlagwörter: variational autoencoder, generative adversarial network, progressive neural network, generation, reconstruction, voxel, Chemical technology, TP1-1185

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1424-8220/24/3/751; https://doaj.org/toc/1424-8220

Zugangs-URL: https://doaj.org/article/f459b8ab4409474daf8991a232751c7c

Cascade stacked autoencoder neural network for intrusion detection in CAN-FD vehicular network.

Autoren: Devi, V. Anjana Reddy, P.V. Bhaskar Ponnada, Sreenu et al.

Quelle: Knowledge-Based Systems. Nov2025:Part A, Vol. 329, pN.PAG-N.PAG. 1p.

Schlagwörter: *INTRUSION detection systems (Computer security), *DEEP learning, *INTELLIGENT transportation systems, *AUTOENCODERS, *CONTROLLER area network (Computer network), *SECURITY systems, *FEATURE selection, RESEARCH evaluation

Embedding of FDA Approved Drugs in Chemical Space Using Cascade Autoencoder with Metric Learning

Autoren: Jungwoo Kim Sangsoo Lim Sangseon Lee et al.

Quelle: 2022 IEEE International Conference on Big Data and Smart Computing (BigComp). :363-365

Stacked encoded cascade error feedback deep extreme learning machine network for manufacturing order completion time.

Autoren: Khan, Waqar Ahmed Masoud, Mahmoud Eltoukhy, Abdelrahman E. E. et al.

Quelle: Journal of Intelligent Manufacturing. Feb2025, Vol. 36 Issue 2, p1313-1339. 27p.

Schlagwörter: *PRODUCTION planning, EXTREME learning machines, AUTOENCODERS, ERROR functions, NETWORK performance

CDAE: A Cascade of Denoising Autoencoders for Noise Reduction in the Clustering of Single-Particle Cryo-EM Images

Autoren: Houchao Lei Yang Yang

Quelle: Frontiers in Genetics, Vol 11 (2021)

Schlagwörter: cryo-EM, autoencoder, image denoising, clustering, deep learning, Genetics, QH426-470

Dateibeschreibung: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fgene.2020.627746/full; https://doaj.org/toc/1664-8021

Zugangs-URL: https://doaj.org/article/b6c4add6a8b2425a989cefc397914165

Cascade Decoders-Based Autoencoders for Image Reconstruction

Autoren: Li, Honggui Galayko, Dimitri Trocan, Maria et al.

Index Begriffe: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2107.00002

HD-CAE: hybrid encoding and deformable decoding autoencoder with cascade attention for visual anomaly detection.

Autoren: Chouhan, Santosh Prakash Bhattacharya, Mahua Sharma, Gopal Krishna

Quelle: Signal, Image & Video Processing; Jul2025, Vol. 19 Issue 7, p1-16, 16p

An Efficient Acoustic Metamaterial Design Approach Integrating Attention Mechanisms and Autoencoder Networks.

Autoren: Chu, Yangyang Liu, Yiping Wang, Bingke et al.

Quelle: Crystals (2073-4352); Jun2025, Vol. 15 Issue 6, p499, 18p

Schlagwörter: ARTIFICIAL neural networks, CONVOLUTIONAL neural networks, AUTOENCODERS, DEEP learning, CASCADE connections

A Deep Cascade Architecture for Stroke Lesion Segmentation and Synthetic Parametric Map Generation over CT Studies.

Alternate Title: Arquitectura profunda en cascada para la segmentación de lesiones de accidente cerebrovascular y la generación de mapas paramétricos sintéticos sobre estudios de TC.

Autoren: Florez, Sebastian Gómez, Santiago Garcia, Julian et al.

Quelle: International Journal of Psychological Research. 2024, Vol. 17 Issue 2, p47-53. 7p.

Schlagwörter: *COMPUTED tomography, *AUTOENCODERS, *CAUSES of death, *PERFUSION, *PROGNOSIS

A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation

Autoren: Lyu, Chenggang Shu, Hai

Index Begriffe: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2011.02881

A dual-level interactive cascade network for agricultural machinery trajectory operation mode identification.

Autoren: Zhai, Weixin Zhang, Xinyu Liu, Jinming et al.

Quelle: Computers & Electronics in Agriculture. Nov2025, Vol. 238, pN.PAG-N.PAG. 1p.

Schlagwörter: *TRAJECTORIES (Mechanics), *FEATURE extraction, *AUTOENCODERS, *AGRICULTURAL equipment, *SUPERVISED learning, *MACHINE learning, *INFORMATION modeling

Detection of Selfish Node in Mobile Ad Hoc Network by Adaptive Multi‐Serial Cascaded Network.

Autoren: Sudhaakar, K. Meena Abarna, K. T. Mohan, E.

Quelle: International Journal of Communication Systems. 5/10/2025, Vol. 38 Issue 7, p1-22. 22p.

Schlagwörter: *CASCADE connections, *CAPSULE neural networks, *AUTOENCODERS, *DEEP learning, *TIME-varying networks, *AD hoc computer networks

Novel PV Fault Diagnoses via SAE and Improved Multi-Grained Cascade Forest With String Voltage and Currents Measures

Autoren: Wei Gao Rong-Jong Wai Shi-Qun Chen

Quelle: IEEE Access, Vol 8, Pp 133144-133160 (2020)

Schlagwörter: Photovoltaic, fault diagnosis, stacked autoencoder, improved multi-grained cascade forest, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/9144195/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/401fc3b6560c48fea42f112d505f54aa

IMU-CNN: implementing remote sensing image restoration framework based on Mask-Upgraded Cascade R-CNN and deep autoencoder.

Autoren: Dewangan, Somesh Kumar Choubey, Siddharth Patra, Jyotiprakash et al.

Quelle: Multimedia Tools & Applications; Aug2024, Vol. 83 Issue 27, p69049-69081, 33p

Schlagwörter: REMOTE sensing, IMAGING systems, IMAGE reconstruction, COMPUTATIONAL complexity, RESEARCH personnel

TV-CCANM: a transformer variational inference in confounding cascade additive noise model for causal effect estimation.

Autoren: Ahmad, Sohail Wang, Hong

Quelle: Journal of Statistical Computation & Simulation. Sep2025, Vol. 95 Issue 14, p3048-3076. 29p.

Schlagwörter: *CAUSAL inference, *CAUSAL models

Kick: Shift-N-Overlap Cascades of Transposed Convolutional Layer for Better Autoencoding Reconstruction on Remote Sensing Imagery

Autoren: Seungkyun Hong Sa-Kwang Song

Quelle: IEEE Access, Vol 8, Pp 107244-107259 (2020)

Schlagwörter: Deconvolutional layer, convolutional autoencoder, adversarial autoencoder, image reconstruction, checkerboard artifact, satellite observation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/9110496/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/f744eaf9ffb8416c867ef58ec405a6ae