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   Articles with "convlstm" as a keyword



Skeleton-based human activity recognition using ConvLSTM and guided feature learning

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recommendations! Published in 2021 at "Soft Computing"

DOI: 10.1007/s00500-021-06238-7

Abstract: Human activity recognition aims to determine actions performed by a human in an image or video. Examples of human activity include standing, running, sitting, sleeping, etc. These activities may involve intricate motion patterns and undesired… read more here.

Keywords: activity recognition; convlstm; human activity; skeleton ... See more keywords
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FACLSTM: ConvLSTM with focused attention for scene text recognition

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recommendations! Published in 2020 at "Science China Information Sciences"

DOI: 10.1007/s11432-019-2713-1

Abstract: Scene text recognition has recently been widely treated as a sequence-to-sequence prediction problem, where traditional fully-connected-LSTM (FC-LSTM) has played a critical role. Owing to the limitation of FC-LSTM, existing methods have to convert 2-D feature… read more here.

Keywords: convlstm; scene; attention; text recognition ... See more keywords

Unsupervised Anomaly Video Detection via a Double-Flow ConvLSTM Variational Autoencoder

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3165977

Abstract: With the rapid increase of video surveillance points in the market in recent years, video anomaly detection has gained extensive attention in the security field. At present, the distribution of normal and anomalous data is… read more here.

Keywords: unsupervised anomaly; detection; convlstm; variational autoencoder ... See more keywords

Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data

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recommendations! Published in 2020 at "IEEE Transactions on Medical Imaging"

DOI: 10.1109/tmi.2019.2943841

Abstract: Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment management and surgical planning. Recent advances of convolutional networks (ConvNets) have demonstrated higher accuracy than traditional mathematical… read more here.

Keywords: patient; convlstm; spatio temporal; tumor growth ... See more keywords

Fully Tensorized Lightweight ConvLSTM Neural Networks for Hyperspectral Image Classification

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recommendations! Published in 2024 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2024.3511575

Abstract: Convolutional long short-term memory (ConvLSTM) possesses a remarkable capability of encoding spatial information and capturing long-range dependencies in sequential data. As a result, ConvLSTM has garnered success in hyperspectral image (HSI) classification. Nonetheless, the design… read more here.

Keywords: classification; fully tensorized; hyperspectral image; convlstm ... See more keywords

Effect of hyper-parameters on the performance of ConvLSTM based deep neural network in crop classification

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recommendations! Published in 2023 at "PLOS ONE"

DOI: 10.1371/journal.pone.0275653

Abstract: Deep learning based data driven methods with multi-sensors spectro-temporal data are widely used for pattern identification and land-cover classification in remote sensing domain. However, adjusting the right tuning for the deep learning models is extremely… read more here.

Keywords: classification; convlstm; deep learning; model ... See more keywords

Geopolitical Risk and Country-Level CO2 Emissions: A Deep Learning Approach Comparing LSTM, CNN and ConvLSTM

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recommendations! Published in 2025 at "International Journal of Energy Economics and Policy"

DOI: 10.32479/ijeep.17764

Abstract: The investigation in this research employs advanced deep learning methods to analyze the bidirectional relationship between geopolitical risks and CO2 emissions in China, India, and the USA across the timeframe of 1990 to 2019. Data… read more here.

Keywords: deep learning; country; geopolitical risks; co2 emissions ... See more keywords

Contribution of Atmospheric Factors in Predicting Sea Surface Temperature in the East China Sea Using the Random Forest and SA-ConvLSTM Model

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recommendations! Published in 2024 at "Atmosphere"

DOI: 10.3390/atmos15060670

Abstract: Atmospheric forcings are significant physical factors that influence the variation of sea surface temperature (SST) and are often used as essential input variables for ocean numerical models. However, their contribution to the prediction of SST… read more here.

Keywords: temperature; sst; random forest; model ... See more keywords

ED-SA-ConvLSTM: A Novel Spatiotemporal Prediction Model and Its Application in Ionospheric TEC Prediction

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recommendations! Published in 2025 at "Mathematics"

DOI: 10.3390/math13121986

Abstract: The ionospheric total electron content (TEC) has complex spatiotemporal variations, making its spatiotemporal prediction challenging. Capturing long-range spatial dependencies is of great significance for improving the spatiotemporal prediction accuracy of TEC. Existing work based on… read more here.

Keywords: tec; spatiotemporal prediction; prediction; model ... See more keywords