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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
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
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 ...
Artículo
Asynchronous dual-pipeline deep learning framework for online data stream classification
(IOS Press, 2020)
Data streaming classification has become an essential task in many fields where real-time decisions have to be made based on incoming information. Neural networks are a particularly suitable technique for the streaming ...
Artículo
Use of Deep Learning Architectures for Day-Ahead Electricity Price Forecasting over Different Time Periods in the Spanish Electricity Market
(MDPI, 2021)
The importance of electricity in people’s daily lives has made it an indispensable commodity in society. In electricity market, the price of electricity is the most important factor for each of those involved in it, ...
Artículo
How efficient deep-learning object detectors are?
(Elsevier, 2020)
Deep-learning object-detection architectures are gaining attraction, as they are used for critical tasks in relevant environments such as health, self-driving, industry, security, and robots. Notwithstanding, the available ...
Artículo
Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model
(Mary Ann Liebert, 2020)
This study proposes a novel bioinspired metaheuristic simulating how the coronavirus spreads and infects healthy people. From a primary infected individual (patient zero), the coronavirus rapidly infects new victims, ...
Artículo
Deep Learning Techniques to Improve the Performance of Olive Oil Classification
(Frontiers Editorial, 2020)
The olive oil assessment involves the use of a standardized sensory analysis according to the “panel test” method. However, there is an important interest to design novel strategies based on the use of Gas Chromatography ...