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Mostrando ítems 1-10 de 28
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 ...
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 ...
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 ...
Artículo
Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance
(Elsevier, 2021)
Object detection has been one of the most active topics in computer vision for the past years. Recent works have mainly focused on pushing the state-of-the-art in the general-purpose COCO benchmark. However, the use of ...
Artículo
Real-time gun detection in CCTV: An open problem
(Elsevier, 2020-12)
Object detectors have improved in recent years, obtaining better results and faster inference time. However, small object detection is still a problem that has not yet a definitive solution. The autonomous weapons detection ...