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Mostrando ítems 1-10 de 37
Artículo
CrimeNet: Neural Structured Learning using Vision Transformer for violence detection
(Elsevier, 2023-04-01)
The state of the art in violence detection in videos has improved in recent years thanks to deep learning models, but it is still below 90% of average precision in the most complex datasets, which may pose a problem of ...
Artículo
Two deep learning approaches to forecasting disaggregated freight flows: convolutional and encoder–decoder recurrent
(Springer, 2021)
Time series forecasting of disaggregated freight flow is a key issue in decision-making by port authorities. For this purpose and to test new deep learning techniques we have selected seven time series of imported goods ...
Ponencia
Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals
(Springer Link, 2023-09)
This paper explores the use of deep learning techniques for detecting sleep apnea. Sleep apnea is a common sleep disorder characterized by abnormal breathing pauses or infrequent breathing during sleep. The current standard ...
Artículo
An Experimental Review on Deep Learning Architectures for Time Series Forecasting
(World Scientific, 2021)
In recent years, deep learning techniques have outperformed traditional models in many machine learning tasks. Deep neural networks have successfully been applied to address time series forecasting problems, which is a ...
Artículo
Comparing artificial intelligence strategies for early sepsis detection in the ICU: an experimental study
(Springer, 2023)
Sepsis is a life-threatening condition whose early recognition is key to improving outcomes for patients in intensive care units (ICUs). Artificial intelligence can play a crucial role in mining and exploiting health data ...
Artículo
A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks
(MDPI, 2019)
Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques ...
Artículo
CrimeNet: Neural Structured Learning using Vision Transformer for violence detection
(Elsevier, 2023-02-02)
The state of the art in violence detection in videos has improved in recent years thanks to deep learning models, but it is still below 90% of average precision in the most complex datasets, which may pose a problem of ...
Artículo
On the Performance of One-Stage and Two-Stage Object Detectors in Autonomous Vehicles Using Camera Data
(MDPI, 2021)
Object detection using remote sensing data is a key task of the perception systems of self-driving vehicles. While many generic deep learning architectures have been proposed for this problem, there is little guidance ...
Ponencia
A Preliminary Study of the Suitability of Deep Learning to Improve LiDAR-Derived Biomass Estimation
(Springer, 2016)
Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information about forest structure. Bio physical models have taken advantage of the use of LiDAR-derived infor mation to improve ...
Artículo
Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods
(Elsevier, 2018-03-01)
This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural ...