Suchergebnisse - "encoder-decoder framework"

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

Autoren: Wang, Zhenwu Liu, Fanghan Han, Mengjie et al.

Quelle: Information Sciences. 661

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

Dateibeschreibung: electronic

Zugangs-URL: 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

Autoren: Zhixuan Zeng Minjie Lin Yang Liu et al.

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

Schlagwörter: 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

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/a60214a654d445a59553f884efa96554

A Lightweight Encoder-Decoder Framework for Carpooling Route Planning

Autoren: Yucen Gao Li Ma Zhemeng Yu et al.

Quelle: 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

Autoren: Qianxia Cao Zhenyu Shan Chenxi Liu et al.

Quelle: 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

Autoren: Hu Zhang Zhaohui Tang Yongfang Xie et al.

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

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40215142

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

Autoren: Yuan Tian Ruonan Cui Wenlong Fu et al.

Quelle: Water Resources Management. 39:4509-4538

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

Autoren: Lina S. Bucher Ahmad Neishabouri Luke Voss et al.

Quelle: Radiotherapy and Oncology. 206:S2708-S2710

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

Autoren: Md Mijanur Rahman Ashik Uzzaman Sadia Islam Sami et al.

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

Schlagwörter: 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

Zugangs-URL: https://doaj.org/article/001e687ba77043448ca1cedb1259dc7d

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

Autoren: Dinesh Kumar Murugan Rajkumar Joseph Nithyanandan Kanagaraj

Quelle: Advanced Photonics Research.

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

Autoren: Upasana Panigrahi Smita Rani Parija Prabodh Kumar Sahoo et al.

Quelle: 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

Autoren: Jiale Zhu Liang Yao Fan Liu et al.

Quelle: 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

Autoren: Yaoxi Zhu Hongbo Li Bingxin Cao et al.

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

Schlagwörter: 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

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40195399
https://doaj.org/article/bf5a61cd628a48edacb57316310c0da4

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

Autoren: Vamsi Krishna Puli Biao Huang

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

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

Autoren: Yuan Tian Wenlong Fu Yajing Dong et al.

Quelle: Earth Science Informatics. 18

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

Autoren: Siguo Wang Zhipeng Li Qinhu Zhang

Quelle: Communications in Computer and Information Science ISBN: 9789819619061

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

Autoren: Zefeng Li Yuehu Liu Yonghong Song

Quelle: 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

Autoren: Haoxiang Xiang Yujie Wang Xingchen Zhang et al.

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

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

Autoren: Fudong Nian Yanhong Gu Wentao Wang et al.

Quelle: Multimedia Systems. 31

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

Autoren: Shamsul Haq Prabal Verma

Quelle: Arabian Journal for Science and Engineering.

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

Autoren: Cheng, Qi Liu, Licheng Zhang, Yao et al.

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

Zugangs-URL: http://arxiv.org/abs/2505.06266