Výsledky vyhľadávania - "encoder–decoder framework"

PML-ED: A method of partial multi-label learning by using encoder-decoder framework and exploring label correlation

Autori: Wang, Zhenwu Liu, Fanghan Han, Mengjie a ďalší

Zdroj: Information Sciences. 661

Predmety: Partial multi-label learning, Label correlation, Label disambiguation, Encoder-Decoder framework, Conditional layer normalization

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:du-47973
https://doi.org/10.1016/j.ins.2024.120165

HET-VQVAE: a novel encoder-decoder framework for irregularly-sampled multivariate time series of patients

Autori: Zhixuan Zeng Minjie Lin Yang Liu a ďalší

Zdroj: Journal of Big Data, Vol 12, Iss 1, Pp 1-21 (2025)

Predmety: Encoder-decoder framework, Attention mechanism, Time embeddings, Latent states, Irregularly-sampled multivariate time series, Interpolation, Computer engineering. Computer hardware, TK7885-7895, Information technology, T58.5-58.64, Electronic computers. Computer science, QA75.5-76.95

Popis súboru: electronic resource

Relation: https://doaj.org/toc/2196-1115

Prístupová URL adresa: https://doaj.org/article/a60214a654d445a59553f884efa96554

A Lightweight Encoder-Decoder Framework for Carpooling Route Planning

Autori: Yucen Gao Li Ma Zhemeng Yu a ďalší

Zdroj: IEEE Transactions on Mobile Computing. 24:7866-7879

Attention-Based Feature Fusion Empowered Encoder-Decoder Framework for Nighttime Traffic Perception From High-Altitude Surveillance System

Autori: Qianxia Cao Zhenyu Shan Chenxi Liu a ďalší

Zdroj: IEEE Transactions on Intelligent Transportation Systems. 26:10850-10864

Multihorizon KPI Forecasting in Complex Industrial Processes: An Adaptive Encoder–Decoder Framework With Partial Teacher Forcing

Autori: Hu Zhang Zhaohui Tang Yongfang Xie a ďalší

Zdroj: IEEE Transactions on Cybernetics. 55:2705-2718

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40215142

Dual-modality Encoder-decoder Framework for Urban Real-time Rainfall-runoff Prediction

Autori: Yuan Tian Ruonan Cui Wenlong Fu a ďalší

Zdroj: Water Resources Management. 39:4509-4538

4222 Comparing sequential DNN models in convolutional encoder-decoder framework for proton dose calculation

Autori: Lina S. Bucher Ahmad Neishabouri Luke Voss a ďalší

Zdroj: Radiotherapy and Oncology. 206:S2708-S2710

A comprehensive construction of deep neural network‐based encoder–decoder framework for automatic image captioning systems

Autori: Md Mijanur Rahman Ashik Uzzaman Sadia Islam Sami a ďalší

Zdroj: IET Image Processing, Vol 18, Iss 14, Pp 4778-4798 (2024)

Predmety: Pre‐trained VGG‐19 Model, QA76.75-76.765, 0209 industrial biotechnology, Deep Learning, Image Feature Extractor, Photography, 0202 electrical engineering, electronic engineering, information engineering, Image Captioning, Computer software, 02 engineering and technology, LSTM Decoder, TR1-1050, CNN Encoder

Prístupová URL adresa: https://doaj.org/article/001e687ba77043448ca1cedb1259dc7d

Transformer Encoder–Decoder Framework for Nonlinear Pulse Evolution and Inverse Modeling

Autori: Dinesh Kumar Murugan Rajkumar Joseph Nithyanandan Kanagaraj

Zdroj: Advanced Photonics Research.

Multi-Scale Moving Object Detection in Complex Video Using a Modified Encoder-Decoder Framework

Autori: Upasana Panigrahi Smita Rani Parija Prabodh Kumar Sahoo a ďalší

Zdroj: 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES). :1-5

A Encoder-Decoder Framework for Foundation Model-based Remote Sensing Semantic Segmentation

Autori: Jiale Zhu Liang Yao Fan Liu a ďalší

Zdroj: Proceedings of the 6th ACM International Conference on Multimedia in Asia Workshops. :1-7

A novel hybrid layer-based encoder–decoder framework for 3D segmentation in congenital heart disease

Autori: Yaoxi Zhu Hongbo Li Bingxin Cao a ďalší

Zdroj: Sci Rep
Scientific Reports, Vol 15, Iss 1, Pp 1-10 (2025)

Predmety: Heart Defects, Congenital, Science, Deep learning, Heart, Hybrid architectures, Article, Imaging, Three-Dimensional, Deep Learning, 3D CT image, Image Processing, Computer-Assisted, Medicine, Humans, Algorithms, Congenital heart disease, Cardiac segmentation

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/40195399
https://doaj.org/article/bf5a61cd628a48edacb57316310c0da4

Nonlinear Slow Feature Analysis for Oscillating Characteristics Under Deep Encoder-Decoder Framework

Autori: Vamsi Krishna Puli Biao Huang

Zdroj: IEEE Transactions on Industrial Informatics. 20:9568-9578

Global to local: a novel encoder-decoder framework for urban real-time rainfall-runoff forecasting

Autori: Yuan Tian Wenlong Fu Yajing Dong a ďalší

Zdroj: Earth Science Informatics. 18

Predicting Transcription Factor Binding Signals Based on a Novel Encoder-Decoder Framework

Autori: Siguo Wang Zhipeng Li Qinhu Zhang

Zdroj: Communications in Computer and Information Science ISBN: 9789819619061

Image Caption Method from Coarse to Fine Based On Dual Encoder-Decoder Framework

Autori: Zefeng Li Yuehu Liu Yonghong Song

Zdroj: 2024 International Joint Conference on Neural Networks (IJCNN). :1-8

Two-Level Battery Health Diagnosis Using Encoder–Decoder Framework and Gaussian Mixture Ensemble Learning Based on Relaxation Voltage

Autori: Haoxiang Xiang Yujie Wang Xingchen Zhang a ďalší

Zdroj: IEEE Transactions on Transportation Electrification. 10:3966-3975

Rwkv-vg: visual grounding with RWKV-driven encoder-decoder framework

Autori: Fudong Nian Yanhong Gu Wentao Wang a ďalší

Zdroj: Multimedia Systems. 31

Edge-Cloud-Assisted Multivariate Time Series Data-Based VAR and Sequential Encoder–Decoder Framework for Multi-Disease Prediction

Autori: Shamsul Haq Prabal Verma

Zdroj: Arabian Journal for Science and Engineering.

Knowledge Guided Encoder-Decoder Framework: Integrating Multiple Physical Models for Agricultural Ecosystem Modeling

Autori: Cheng, Qi Liu, Licheng Zhang, Yao a ďalší

Predmety: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Machine Learning (cs.LG)

Prístupová URL adresa: http://arxiv.org/abs/2505.06266