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Mostrando ítems 1-10 de 19
Artículo
Filter‑based feature selection in the context of evolutionary neural networks in supervised machine learning
(Springer, 2020)
This paper presents a workbench to get simple neural classifcation models based on product evolutionary networks via a prior data preparation at attribute level by means of flter-based feature selection. Therefore, the ...
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
Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance
(Elsevier, 2020)
Breast cancer is the most frequent cancer in women and the second most frequent overall after lung cancer. Although the 5-year survival rate of breast cancer is relatively high, recurrence is also common which often ...
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 ...
Ponencia
Concept Drift Detection to Improve Time Series Forecasting of Wind Energy Generation
(Springer, 2022)
Most of the current data sources generate large amounts of data over time. Renewable energy generation is one example of such data sources. Machine learning is often applied to forecast time series. Since data flows are ...
Artículo
Statistically Representative Metrology of Nanoparticles via Unsupervised Machine Learning of TEM Images
(MDPI, 2021)
The morphology of nanoparticles governs their properties for a range of important applica tions. Thus, the ability to statistically correlate this key particle performance parameter is paramount in achieving accurate ...
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 ...
Tesis Doctoral
Deep learning for enhancing object detection in autonomous driving
(2022-06-20)
Autonomous driving is one of the most important technological challenges of this century. Its development will revolutionize mobility and solve many problems associated with it. The popularity of self-driving vehicles is ...
Artículo
Object detection using depth completion and camera-LiDAR fusion for autonomous driving
(IOS Press, 2022)
Autonomous vehicles are equipped with complimentary sensors to perceive the environment accurately. Deep learning models have proven to be the most effective approach for computer vision problems. Therefore, in autonomous ...
Artículo
A data mining based clinical decision support system for survival in lung cancer
(Via Médica Journals, 2021)
Background: A clinical decision support system (CDSS) has been designed to predict the outcome (overall survival) by extracting and analyzing information from routine clinical activity as a complement to clinical guidelines ...