Apr 29, 2019 · The proposed approach consists of an encoder–decoder network with convolutional long short-term memory (LSTM) units. Optical flow is calculated ...

Jan 17, 2024 · The proposed approach consists of an encoder-decoder network with convolutional long short-term memory (LSTM) units. Optical flow is calculated ...

Mar 31, 2019 · Data for Prediction of Sea Ice Motion with Convolutional Long Short-Term Memory Networks · Abstract · Dataset Files · QUESTIONS?

Abstract—Prediction of sea ice motion is important for safe- guarding human activities in polar regions, such as ship naviga-.

To address the challenge, in this study, we proposed a novel approach for predicting sea ice motion in the upcoming days using the Self-Attention Convolutional ...

jozefowicz, An empirical exploration of recurrent network architectures, J Mach Learn Res, № 37, с. · tieleman, Lecture 6.5-rmsprop: Divide the gradient by a ...

Data for Prediction of Sea Ice Motion with Convolutional Long Short-Term Memory Networks. This is the images and the image masks used in the paper "Z.

... prediction model of sea ice concentration (SIC) based on the convolutional long short-term memory network (ConvLSTM) algorithm was proposed in this study.

In this study, we propose a deep learning approach, namely convolutional long short-term memory networks (ConvLSTM), to forecast sea ice in the Barents Sea at ...

Data for Prediction of Sea Ice Motion with Convolutional Long Short-Term Memory Networks. This is the images and the image masks used in the paper "Z. Petrou ...