A Deep Learning Approach to Radar Extrapolation

[1]  Yunbo Wang,et al.  Eidetic 3D LSTM: A Model for Video Prediction and Beyond , 2019, ICLR.

[2]  Razvan Pascanu,et al.  On the difficulty of training recurrent neural networks , 2012, ICML.

[3]  Hidetomo Sakaino,et al.  Spatio-Temporal Image Pattern Prediction Method Based on a Physical Model With Time-Varying Optical Flow , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Juanzhen Sun,et al.  Use of NWP for Nowcasting Convective Precipitation: Recent Progress and Challenges , 2014 .

[5]  Philip S. Yu,et al.  PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning , 2018, ICML.

[6]  Shouling Ji,et al.  Spreading social influence with both positive and negative opinions in online networks , 2019, Big Data Min. Anal..

[7]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.

[8]  Ching-Hsien Hsu,et al.  Service Composition in Cyber-Physical-Social Systems , 2020, IEEE Transactions on Emerging Topics in Computing.

[9]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[10]  W. Woo Application of Optical Flow Techniques to Rainfall Nowcasting , 2014 .

[11]  Gabriel Kreiman,et al.  Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning , 2016, ICLR.

[12]  Andrew Zisserman,et al.  Two-Stream Convolutional Networks for Action Recognition in Videos , 2014, NIPS.

[13]  Yann LeCun,et al.  Deep multi-scale video prediction beyond mean square error , 2015, ICLR.

[14]  Seunghoon Hong,et al.  Decomposing Motion and Content for Natural Video Sequence Prediction , 2017, ICLR.

[15]  Quoc V. Le,et al.  Sequence to Sequence Learning with Neural Networks , 2014, NIPS.

[16]  Marc'Aurelio Ranzato,et al.  Video (language) modeling: a baseline for generative models of natural videos , 2014, ArXiv.

[17]  Maninder Singh,et al.  Big data analytics for healthcare industry: impact, applications, and tools , 2019, Big Data Min. Anal..

[18]  Nitish Srivastava,et al.  Unsupervised Learning of Video Representations using LSTMs , 2015, ICML.

[19]  Dit-Yan Yeung,et al.  Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting , 2015, NIPS.

[20]  Guangchun Luo,et al.  Disseminating authorized content via data analysis in opportunistic social networks , 2019, Big Data Min. Anal..

[21]  Trevor Darrell,et al.  Long-term recurrent convolutional networks for visual recognition and description , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[22]  Junlong Zhou,et al.  Security-Critical Energy-Aware Task Scheduling for Heterogeneous Real-Time MPSoCs in IoT , 2020, IEEE Transactions on Services Computing.

[23]  Philip S. Yu,et al.  PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs , 2017, NIPS.

[24]  I. Zawadzki,et al.  Scale-Dependence of the Predictability of Precipitation from Continental Radar Images. Part I: Description of the Methodology , 2002 .

[25]  Sukhendu Das,et al.  Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks , 2017, NIPS.

[26]  Rob Fergus,et al.  Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks , 2015, NIPS.

[27]  Fei-Fei Li,et al.  Deep visual-semantic alignments for generating image descriptions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[28]  Dit-Yan Yeung,et al.  Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model , 2017, NIPS.