Výsledky vyhledávání - "complex-valued convolutional autoencoder"

An Attention Based Complex-valued Convolutional Autoencoder for GEO SA-Bi SAR Ship Target Refocusing

Autoři: Meng Lian Miodrag Bolic

Zdroj: 2023 IEEE Sensors Applications Symposium (SAS). :1-6

SAR Images Unsupervised Feature Abstraction with A Complex-valued Convolutional Autoencoder

Autoři: Jinling He Sirui Tian Chao Wang a další

Zdroj: 2021 SAR in Big Data Era (BIGSARDATA). :1-4

Přístupová URL adresa: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9574285
http://xplorestaging.ieee.org/ielx7/9574102/9574125/09574285.pdf?arnumber=9574285

Complex-Valued Convolutional Autoencoder and Spatial Pixel-Squares Refinement for Polarimetric SAR Image Classification

Autoři: Ronghua Shang Guangguang Wang Michael A. Okoth a další

Zdroj: Remote Sensing, Vol 11, Iss 5, p 522 (2019)

Témata: complex-valued convolutional autoencoder, PolSAR image classification, spatial pixel-squares refinement, deep learning, Science

Popis souboru: electronic resource

Relation: http://www.mdpi.com/2072-4292/11/5/522; https://doaj.org/toc/2072-4292

Přístupová URL adresa: https://doaj.org/article/07bf32964c3942d499337bf71c9e5a9a

Deep-Learning-Based Dictionary Construction for MIMO Radar Detection in Complex Scenes

Autoři: Hongyan Wang He Zhou Qinghua Guo a další

Zdroj: IEEE Internet of Things Journal. 11:12419-12434

Témata: nonlinear correction, Multiple-input multiple-output (MIMO) radar, transceiving space-time resource allocation, sparse representation, complex-valued convolutional autoencoder

Complex-Valued Convolutional Autoencoder and Spatial Pixel-Squares Refinement for Polarimetric SAR Image Classification.

Autoři: Shang, Ronghua Wang, Guangguang A. Okoth, Michael a další

Zdroj: Remote Sensing; 3/1/2019, Vol. 11 Issue 5, p522, 1p

Témata: POLARIMETRIC remote sensing, SYNTHETIC aperture radar, DEEP learning, FEATURE extraction, IMAGING systems

Synthetic Aperture Radar for Geosciences.

Autoři: Meng, Lingsheng Yan, Chi Lv, Suna a další

Zdroj: Reviews of Geophysics; Sep2024, Vol. 62 Issue 3, p1-79, 79p

Témata: SYNTHETIC aperture radar, MACHINE learning, SURFACE of the earth, ENVIRONMENTAL sciences, DEEP learning

Deep Speech Denoising with Minimal Dependence on Clean Speech Data.

Autoři: Poluboina, Venkateswarlu Pulikala, Aparna Pitchaimuthu, Arivudai Nambi

Zdroj: Circuits, Systems & Signal Processing; Jun2024, Vol. 43 Issue 6, p3909-3926, 18p

Témata: DATA scrubbing, AUTOMATIC speech recognition, DEEP learning, SPEECH enhancement, ACQUISITION of data

A Multicomponent Linear Frequency Modulation Signal-Separation Network for Multi-Moving-Target Imaging in the SAR-Ground-Moving-Target Indication System.

Autoři: Ding, Chang Mu, Huilin Zhang, Yun

Zdroj: Remote Sensing; Feb2024, Vol. 16 Issue 4, p605, 20p

Témata: SPACE-based radar, SYNTHETIC aperture radar, PARAMETER estimation, IMAGING systems

Polarimetric Imaging via Deep Learning: A Review.

Autoři: Li, Xiaobo Yan, Lei Qi, Pengfei a další

Zdroj: Remote Sensing; Mar2023, Vol. 15 Issue 6, p1540, 42p

Témata: DEEP learning, POLARIMETRY, IMAGE reconstruction, REMOTE sensing, IMAGE fusion, CONVOLUTIONAL neural networks, SYNTHETIC aperture radar

Evaluation of deep learning and transform domain feature extraction techniques for land cover classification: balancing through augmentation.

Autoři: Parikh, Hemani Patel, Samir Patel, Vibha

Zdroj: Environmental Science & Pollution Research; Feb2023, Vol. 30 Issue 6, p14464-14483, 20p

Témata: LAND cover, EXTRACTION techniques, FEATURE extraction, DEEP learning, GRASSLANDS, FORESTS & forestry

Complex-Valued Autoencoders with Coherence Preservation for SAR

Autoři: Mohammadi Asiyabi, Reza orcid:0000-0002-0162- Datcu, Mihai a další

Témata: MENELAOS_NT, H2020, Sensor Systems, Signal Processing, Information Extraction, Synthetic Aperture Radar, Complex-Valued Autoencoders, Phase Coherency Preservation

Relation: https://zenodo.org/communities/menelaos-nt/; https://zenodo.org/communities/eu/; https://zenodo.org/records/8089890; oai:zenodo.org:8089890; https://doi.org/10.5281/zenodo.8089890

Dostupnost: https://doi.org/10.5281/zenodo.8089890
https://zenodo.org/records/8089890

An Innovative Supervised Classification Algorithm for PolSAR Image Based on Mixture Model and MRF.

Autoři: Liu, Mingliang Deng, Yunkai Han, Chuanzhao a další

Zdroj: Remote Sensing; Nov2022, Vol. 14 Issue 21, p5506, 22p

Témata: CLASSIFICATION algorithms, SYNTHETIC aperture radar, DISTRIBUTION (Probability theory), PIXELS, SYNTHETIC apertures, RANDOM fields, MIXTURES

SNR Enhancement for Multi-TE MRSI Using Joint Low-Dimensional Model and Spatial Constraints.

Autoři: Li, Yahang Wang, Zepeng Lam, Fan

Zdroj: IEEE Transactions on Biomedical Engineering; Oct2022, Vol. 69 Issue 10, p3087-3097, 11p

Témata: NOISE control, SPECTROSCOPIC imaging, SIGNAL-to-noise ratio, MAGNETIC resonance imaging, CONVOLUTIONAL neural networks

How to Identify Patterns of Citywide Dynamic Traffic at a Low Cost? An In-Depth Neural Network Approach with Digital Maps.

Autoři: Zhang, Li Gong, Ke Xu, Maozeng a další

Zdroj: Complexity; 5/24/2021, p1-15, 15p

Témata: DIGITAL maps, DIGITAL mapping, CITY traffic, TRAFFIC patterns, TRAFFIC engineering

Geografický termín: CHONGQING (China)

Deep complex neural network applications in remote sensing: an introductory review.

Autoři: Ranney, Kenneth I. Raynal, Ann M. Dash, Bibhas Nalinikanta a další

Zdroj: Proceedings of SPIE; 3/15/2021, Vol. 11742, p1174208-1174208, 1p

Learning Rotation Domain Deep Mutual Information Using Convolutional LSTM for Unsupervised PolSAR Image Classification.

Autoři: Wang, Lei Xu, Xin Gui, Rong a další

Zdroj: Remote Sensing; Dec2020, Vol. 12 Issue 24, p4075, 1p

Témata: POLARIMETRY, LONG-term memory, SHORT-term memory, SYNTHETIC aperture radar, SYNTHETIC apertures, DEEP learning, ROTATIONAL motion

Scatter Matrix Based Domain Adaptation for Bi-Temporal Polarimetric SAR Images.

Autoři: Sun, Weidong Li, Pingxiang Du, Bo a další

Zdroj: Remote Sensing; Feb2020, Vol. 12 Issue 4, p658, 1p

Témata: POLARIMETRY, S-matrix theory, SYNTHETIC aperture radar, SYNTHETIC apertures, TIME series analysis, PRINCIPAL components analysis, DISTRIBUTION (Probability theory), KERNEL functions

PolSAR Image Classification with Lightweight 3D Convolutional Networks.

Autoři: Dong, Hongwei Zhang, Lamei Zou, Bin

Zdroj: Remote Sensing; Feb2020, Vol. 12 Issue 3, p396, 1p

Témata: SYNTHETIC apertures, POLARIMETRY, THREE-dimensional display systems, ARTIFICIAL neural networks, IMAGE processing, SYNTHETIC aperture radar, OPTICAL images, MATHEMATICAL convolutions

PolSAR Image Classification via Learned Superpixels and QCNN Integrating Color Features.

Autoři: Zhang, Xinzheng Xia, Jili Tan, Xiaoheng a další

Zdroj: Remote Sensing; Aug2019, Vol. 11 Issue 15, p1831-1831, 1p

Témata: POLARIMETRY, HYPERSPECTRAL imaging systems, PIXELS, SYNTHETIC apertures, COLORS, IMAGE, SYNTHETIC aperture radar

Geografický termín: SAN Francisco (Calif.)