Stock Market Forecasting Based on Spatiotemporal Deep Learning. [PDF]
Entropy (Basel), 2023 This study introduces the Spacetimeformer model, a novel approach for predicting stock prices, leveraging the Transformer architecture with a time–space mechanism to capture both spatial and temporal interactions among stocks. Traditional Long–Short Term
Li YC, Huang HY, Yang NP, Kung YH.
europepmc +4 more sources
A Spatiotemporal Deep Learning Approach for Automatic Pathological Gait Classification. [PDF]
Sensors (Basel), 2021 Human motion analysis provides useful information for the diagnosis and recovery assessment of people suffering from pathologies, such as those affecting the way of walking, i.e., gait. With recent developments in deep learning, state-of-the-art performance can now be achieved using a single 2D-RGB-camera-based gait analysis system, offering an ...
Albuquerque P +3 more
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Spatiotemporal identification of druggable binding sites using deep learning [PDF]
Communications Biology, 2020 Abstract Identification of novel protein binding sites expands druggable genome and opens new opportunities for drug discovery. Generally, presence or absence of a binding site depends on the three-dimensional conformation of a protein, making binding site identification resemble the object detection problem in computer vision.
Igor Kozlovskii, Petr Popov
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Direct video-based spatiotemporal deep learning for cattle lameness detection. [PDF]
Sci RepCattle lameness is a prevalent health problem in livestock farming, often resulting from hoof injuries or infections, and severely impacts animal welfare and productivity. Early and accurate detection is critical for minimizing economic losses and ensuring proper treatment.
Sohan MF +4 more
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BIDL: a brain-inspired deep learning framework for spatiotemporal processing
Frontiers in Neuroscience, 2023 Brain-inspired deep spiking neural network (DSNN) which emulates the function of the biological brain provides an effective approach for event-stream spatiotemporal perception (STP), especially for dynamic vision sensor (DVS) signals. However, there is a
Zhenzhi Wu +9 more
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Embedding physics into deep learning for modeling spatiotemporal systems [PDF]
, 2022 Pu Ren
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Multifidelity deep learning modeling of spatiotemporal lung mechanics
Frontiers in PhysiologyIntroductionDigital twins of the respiratory system have shown promise in predicting the patient-specific response of lungs connected to mechanical ventilation.
José Barahona Yáñez +5 more
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Novel Intelligent Spatiotemporal Grid Earthquake Early-Warning Model
Remote Sensing, 2021 The integration analysis of multi-type geospatial information poses challenges to existing spatiotemporal data organization models and analysis models based on deep learning.
Daoye Zhu +5 more
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Visual Analysis of Spatiotemporal Data Predictions with Deep Learning Models
Applied Sciences, 2021 The output of a deep-learning model delivers different predictions depending on the input of the deep learning model. In particular, the input characteristics might affect the output of a deep learning model.
Hyesook Son +5 more
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A Deep Learning Framework for Spatiotemporal Ultrasound Localization Microscopy
IEEE Transactions on Medical Imaging, 2021 Copyright 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted ...
Leo Milecki +8 more
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