Výsledky vyhledávání - "convolutional encoder-decoder neural network"

Hydraulic heterogeneity estimation with transient hydraulic tomography and convolutional encoder-decoder neural network

Autoři: Jui-Pin Tsai Yu-Kai Chen Bo-Tsen Wang a další

Zdroj: Stochastic Environmental Research and Risk Assessment. 39:4083-4105

Underwater Acoustic Signal Noise Reduction Based on a Fully Convolutional Encoder-Decoder Neural Network

Autoři: Yongqiang Song Qian Chu Feng Liu a další

Zdroj: Journal of Ocean University of China. 22:1487-1496

Robust Sarcasm Detection using Artificial Rabbits Optimizer with Multilayer Convolutional Encoder-Decoder Neural Network on Social Media

Autoři: Palaniammal A Anandababu P

Zdroj: International Journal of Electronics and Communication Engineering. 10:1-13

An Attention-Based Multi-Context Convolutional Encoder-Decoder Neural Network for Work Zone Traffic Impact Prediction

Autoři: Jiang, Qinhua Liao, Xishun Gong, Yaofa a další

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, 11. Sustainability, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2405.21045

Anomaly Detection and Segmentation for Wafer Defect Patterns Using Deep Convolutional Encoder–Decoder Neural Network Architectures in Semiconductor Manufacturing

Autoři: Takeshi Nakazawa Deepak V. Kulkarni

Zdroj: IEEE Transactions on Semiconductor Manufacturing. 32:250-256

Témata: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/66/8704169/08634922.pdf
https://ieeexplore.ieee.org/document/8634922

Hydraulic heterogeneity estimation with transient hydraulic tomography and convolutional encoder-decoder neural network.

Autoři: Chen, Yu-Kai Tsai, Jui-Pin Wang, Bo-Tsen a další

Zdroj: Stochastic Environmental Research & Risk Assessment; Sep2025, Vol. 39 Issue 9, p4083-4105, 23p

Témata: HYDRAULIC conductivity, HYDROGEOLOGICAL modeling, AQUIFERS, HYDRAULIC models, MATHEMATICAL optimization, ARTIFICIAL neural networks

A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction

Autoři: Chollampatt, Shamil Ng, Hwee Tou

Témata: Computer Science - Computation and Language, text

URL: http://arxiv.org/abs/1801.08831

Semantic segmentation on remotely sensed images using deep convolutional encoder-decoder neural network

Autoři: Teerapong Panboonyuen

One-Step Time-Dependent Future Video Frame Prediction with a Convolutional Encoder-Decoder Neural Network

Autoři: Silvia-Laura Pintea Vedran Vukotić Jan C. van Gemert a další

Přispěvatelé: Silvia-Laura Pintea Vedran Vukotić Jan C. van Gemert a další

Zdroj: Lecture Notes in Computer Science ISBN: 9783319685595

Témata: future video frame prediction, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, single-image, generative models, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, CNNs, motion prediction, scene understanding, 02 engineering and technology, motion anticipation, appearance prediction, action forecasting, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], motion synthesis, convolutional neural networks, future frame prediction, 0202 electrical engineering, electronic engineering, information engineering, time modeling

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/pdf/1702.04125
http://arxiv.org/abs/1702.04125
https://inria.hal.science/hal-01467064v1
https://inria.hal.science/hal-01567742v1
https://dblp.uni-trier.de/db/journals/corr/corr1702.html#VukoticPRGG17
https://link.springer.com/chapter/10.1007/978-3-319-68560-1_13
https://arxiv.org/abs/1702.04125
https://ui.adsabs.harvard.edu/abs/2017arXiv170204125V/abstract
https://hal.inria.fr/hal-01567742/document
https://hal.inria.fr/hal-01567742

A deep convolutional encoder-decoder neural network in assisting seismic horizon tracking

Autoři: Wu, Hao Zhang, Bo

Témata: Physics - Geophysics, 13. Climate action, FOS: Physical sciences, 01 natural sciences, 0105 earth and related environmental sciences, Geophysics (physics.geo-ph)

Přístupová URL adresa: http://arxiv.org/abs/1804.06814

One-Step Time-Dependent Future Video Frame Prediction with a Convolutional Encoder-Decoder Neural Network

Autoři: Vukotić, Vedran Pintea, Silvia-Laura Raymond, Christian a další

Témata: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/1702.04125

Underwater Acoustic Signal Noise Reduction Based on a Fully Convolutional Encoder-Decoder Neural Network.

Autoři: Song, Yongqiang Chu, Qian Liu, Feng a další

Zdroj: Journal of Ocean University of China; Dec2023, Vol. 22 Issue 6, p1487-1496, 10p

One-Step Time-Dependent Future Video Frame Prediction with a Convolutional Encoder-Decoder Neural Network

Autoři: Vukotić, Vedran Pintea, Silvia-Laura Raymond, Christian a další

Přispěvatelé: Vukotić, Vedran Pintea, Silvia-Laura Raymond, Christian a další

Zdroj: Netherlands Conference on Computer Vision (NCCV) ; https://inria.hal.science/hal-01467064 ; Netherlands Conference on Computer Vision (NCCV), Dec 2016, Lunteren, Netherlands

Témata: action forecasting, future frame prediction, motion prediction, motion anticipation, single-image, time modeling, motion synthesis, generative models, convolutional neural networks, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geografické téma: Lunteren, Netherlands

Dostupnost: https://inria.hal.science/hal-01467064
https://inria.hal.science/hal-01467064v1/document
https://inria.hal.science/hal-01467064v1/file/Vukotic_NCCV_2016.pdf

Anomaly Detection and Segmentation for Wafer Defect Patterns Using Deep Convolutional Encoder–Decoder Neural Network Architectures in Semiconductor Manufacturing.

Autoři: Nakazawa, Takeshi Kulkarni, Deepak V.

Zdroj: IEEE Transactions on Semiconductor Manufacturing; May2019, Vol. 32 Issue 2, p250-256, 7p

Témata: ARTIFICIAL neural networks, SEMICONDUCTOR manufacturing, ARCHITECTURE, SEMICONDUCTOR devices, COMPUTER architecture

Mild Traumatic Brain Injury and Career Stage Associate with Visible Perivascular Spaces in Special Operations Forces Soldiers

Autoři: Powell, Jacob R. Zong, Xiaopeng Weinstein, Joshua M. a další

Zdroj: Annals of Biomedical Engineering

Témata: sleep, blast exposure, soldiers, model, specialization, system, injury, non-parametric Mann-Whitney U test, glymphatic system, deep convolutional encoder-decoder neural networks, members, physiological changes, magnetic resonance imaging, resonance imaging, waste clearance, group differences, Special Operations Forces Soldiers, segments, Special Operations Forces combat soldiers, brain, stage associations, U test, military service members, group, neurobiological outcomes, network, analysis, exposure, mild traumatic brain injury history, convolutional encoder-decoder neural network

Relation: https://cdr.lib.unc.edu/downloads/rb68xs01v?file=thumbnail; https://cdr.lib.unc.edu/downloads/rb68xs01v

Dostupnost: https://doi.org/10.17615/2gv8-am31
https://cdr.lib.unc.edu/downloads/rb68xs01v?file=thumbnail
https://cdr.lib.unc.edu/downloads/rb68xs01v

利用深度全卷积编解码网络的单通道语音增强. (Chinese)

Alternate Title: Single Channel Speech Enhancement Based on Deep Fully Convolutional Encoder-Decoder Neural Network. (English)

Autoři: 时文华 张雄伟 邹霞 a další

Zdroj: Journal of Signal Processing; Apr2019, Vol. 35 Issue 4, p631-640, 10p

Predicting Time-to-Healing from a Digital Wound Image: A Hybrid Neural Network and Decision Tree Approach Improves Performance.

Autoři: Kolli, Aravind Wei, Qi Ramsey, Stephen A.

Zdroj: Computation; Mar2024, Vol. 12 Issue 3, p42, 17p

Témata: WOUND healing, ARTIFICIAL neural networks, DEEP learning, DECISION trees, CHRONIC wounds & injuries, IMAGE segmentation, TISSUE wounds

Interference Motion Removal for Doppler Radar Vital Sign Detection Using Variational Encoder-Decoder Neural Network

Autoři: Czerkawski, Mikolaj Ilioudis, Christos Clemente, Carmine a další

Témata: Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/2404.08298

ADVANCED DEEP LEARNING ARCHITECTURES FOR AUTOMATED SILICON WAFER DEFECT DETECTION WITH SYNTHETIC DATA AUGMENTATION.

Autoři: DEEPTI, KAKARLA

Zdroj: i-Manager's Journal on Electronics Engineering; Dec2025, Vol. 16 Issue 1, p31-41, 11p

Témata: DEEP learning, CONVOLUTIONAL neural networks, DEFECT tracking (Computer software development), SILICON wafers, IMAGE processing, SEMICONDUCTOR industry, DATA augmentation

Symmetric Combined Convolution with Convolutional Long Short-Term Memory for Monaural Speech Enhancement.

Autoři: Xian, Yang Fu, Yujin Xing, Peixu a další

Zdroj: Symmetry (20738994); Oct2025, Vol. 17 Issue 10, p1768, 20p

Témata: SPEECH enhancement, LONG short-term memory, ARTIFICIAL neural networks, FEATURE extraction, SPEECH processing systems, AUDITORY perception