A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is text/html.
Filters
Wind Power Prediction in View of Ramping Events Based on Classified Spatiotemporal Network
2022
Frontiers in Energy Research
Preserved Fulltext
This paper presents a wind power prediction model of ramping events based on classified spatiotemporal network. ...
Combined with the probability weight, the spatiotemporal neural network considering numerical weather prediction data is used to realize power prediction. ...
This paper presents a wind power prediction model of ramping events based on classified spatiotemporal network. ...
doi:10.3389/fenrg.2021.754274
fatcat:5yddfgds5fclnbvern4pwa5odi
Meta-Learning and Self-Supervised Pretraining for Real World Image Translation
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We follow this line of work and explore spatio-temporal structure in a recently introduced image-to-image translation problem in order to: i) formulate a novel multi-task few-shot image generation benchmark ...
deep-learning to the semi-supervised and few-shot domains. ...
ACKNOWLEDGEMENTS The authors acknowledge the MIT SuperCloud and Lincoln Laboratory Supercomputing Center (Reuther et al., 2018) for providing HPC and consultation resources that have contributed to the ...
arXiv:2112.11929v1
fatcat:2a3bjrxr7bfmnkea4cec5oaevm
CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We apply our proposed architecture to two representative, practical use cases that involve point-cloud streams, i.e., mobile service traffic forecasting and air quality indicator forecasting. ...
network models. ...
Acknowledgments This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no.101017109 "DAEMON", and from the Cisco University Research ...
arXiv:1907.12410v3
fatcat:3wea4b2uvjbctnhmfw7v2obgjm
Multi-scale Bushfire Detection from Multi-modal Streams of Remote Sensing Data
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
In this paper, we propose a multi-scale deep neural network model that combines both satellite images and weather data for detecting and locating bushfires at both image and pixel level. ...
adversarial effects. ...
ACKNOWLEDGMENT This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.01-2019.323. ...
doi:10.1109/access.2020.3046649
fatcat:pcoyokt6xnaanpphah3vsy7vye
Graph Neural Networks in IoT: A Survey
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
., convolution neural networks and recurrent neural networks) have been extensively employed in solving IoT tasks by learning patterns from multi-modal sensory data. ...
The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily lives: healthcare, home, transportation, manufacturing, supply chain, and so on. ...
For instance, CMA China [317] provides weather information to aid air quality prediction. ...
arXiv:2203.15935v2
fatcat:jkqg5ukg5fezbewu5mr5hqsp4e
Spatiotemporal Data Mining: A Survey on Challenges and Open Problems
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time. ...
We attempt to fill this gap by providing a comprehensive literature survey on state-of-the-art advances in STDM. ...
[239, 339] proposed hybrid predictive models for air quality prediction combining different predictors, e.g., spatial, temporal, and inflection predictors. ...
arXiv:2103.17128v1
fatcat:ci5pt5bytndr5inolznjsaizpi
2021 Index IEEE Transactions on Intelligent Transportation Systems Vol. 22
2021
IEEE transactions on intelligent transportation systems (Print)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. ...
., +, TITS Dec. 2021 7619-7630 Image quality Haze Removal of Railway Monitoring Images Using Multi-Scale Residual Network. ...
doi:10.1109/tits.2021.3139738
fatcat:p2mkawtrsbaepj4zk24xhyl2oa
2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. ...
., +, JSTARS 2021 8730-8743 SA-JSTN: Self-Attention Joint Spatiotemporal Network for Temperature Forecasting. ...
doi:10.1109/jstars.2022.3143012
fatcat:dnetkulbyvdyne7zxlblmek2qy
A deep generative model for probabilistic energy forecasting in power systems: normalizing flows
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 pre-print arXiv:2106.09370v3 fatcat:qdwgpbfj4ncenhmpsqphe3qugqOther Versions
The models producing weather-based wind, solar power, and load scenarios are properly compared in terms of forecast value by considering the case study of an energy retailer and quality using several complementary ...
networks and variational autoencoders. ...
Nevertheless, the comparison is only based on quality metrics, and the models do not take into account weather forecasts; 2. ...
arXiv:2106.09370v4
fatcat:iyl7tswwarecho7faa6pdnbjo4
SpectraGAN
2021
Proceedings of the 17th International Conference on emerging Networking EXperiments and Technologies
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
City-scale spatiotemporal mobile network traffic data can support numerous applications in and beyond networking. ...
SpectraGAN is an original conditional GAN design with the defining feature of generating spectra of mobile traffic at all locations of the target region based on their contextual features. ...
ACKNOWLEDGMENTS We thank the anonymous shepherd and reviewers for their helpful comments. ...
doi:10.1145/3485983.3494844
fatcat:o53wlbvlazanjhpfh3rws5cbsq
Urban Safety: An Image-Processing and Deep-Learning-Based Intelligent Traffic Management and Control System
2021
Sensors
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Our analysis found that deep-learning-based approaches for short-term traffic state forecast and multi-intersection signal control showed reasonable results, but lacked robustness for unusual scenarios ...
Reliable implementations of ITMC improve the safety of inhabitants and the quality of life, leading to economic growth. ...
and tested an Elman network, a partial RNN, and a TDNN Lacked robustness RMSE: around (8-20)% Bohan and Yun, 2019 [48] Applied a BRNN, LSTM, and GRU for prediction Less and low-quality data MAE of BRNN ...
doi:10.3390/s21227705
pmid:34833794
pmcid:PMC8623406
fatcat:d245ucplzbcwdfukxn2ndgnxii
Learning Neural Textual Representations for Citation Recommendation
2021
2020 25th International Conference on Pattern Recognition (ICPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Features and Multi-View Images
DAY 2 -Jan 13, 2021
Simonsson, Simon; Dias
Casagrande, Flávia; Zouganeli, Evi
2496
Location Prediction in Real Homes of Older Adults based on K-
Means in Low-Resolution ...
Deep Homography-Based Video Stabilization
DAY 2 -Jan 13, 2021
Arsalan, Muhammad; Santra, Avik;
Bierzynski, Kay; Issakov, Vadim
2442
Air-Writing with Sparse Network of Radars Using Spatio-Temporal ...
doi:10.1109/icpr48806.2021.9412725
fatcat:3vge2tpd2zf7jcv5btcixnaikm
A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation
2021
Data Science and Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Third, we focus on three kinds of traffic prediction problems (i.e., classification, generation and estimation/forecasting). ...
Later, we review existing work on the four parts. First, we summarize traffic data into five types according to their difference on spatial and temporal dimensions. ...
., measuring surface temperature using weather balloons), while raster data correspond to traffic or meteorological data collected at fixed ST grids (e.g., air quality of Earth's surface collected by ground-based ...
doi:10.1007/s41019-020-00151-z
fatcat:nnnnxnpo3bgk3l4hpr7kk2n4xa
Transfer Learning with Time Series Data: A Systematic Mapping Study
2021
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This benefits learning in various time series domains, including a variety of domains based on sensor values. ...
Following the review guidelines of Kitchenham and Charters, we identify and analyze 223 relevant publications. We describe the pursued approaches and point out trends. ...
ACKNOWLEDGMENT This work was financially supported by the Munich University of Applied Sciences and the German Research Foundation (DFG) through the "Open Access Publishing" program. ...
doi:10.1109/access.2021.3134628
fatcat:66sxrp35bndjjeffxwy5jisa6q
2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57
2019
IEEE Transactions on Geoscience and Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
., and Drake, V.A., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674 ...
on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T., Wu, Y., Zheng, G., Zhang, D., Zhang, Y., and Li, Y., Tropical Cyclone Center ...
., +, TGRS Feb. 2019 815-828 Classification of Hyperspectral Images Based on Multiclass Spatial-Spectral Generative Adversarial Networks. ...
doi:10.1109/tgrs.2020.2967201
fatcat:kpfxoidv5bgcfo36zfsnxe4aj4
« Previous
Showing results 1 — 15 out of 172 results