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Mostrando ítems 1-10 de 14
Artículo
A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation
(Elsevier, 2017)
Breast cancer is the most common cause of cancer death in women. Today, post-transcriptional protein products of the genes involved in breast cancer can be identified by immunohistochemistry. However, this method has ...
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 ...
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
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
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
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
Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance
(ScienceDirect, 2021-08-18)
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
Creation of Synthetic Data with Conditional Generative Adversarial Networks
(Springer, 2019)
The generation of synthetic data is becoming a fundamental task in the daily life of any organization due to new protection data laws that are emerging. Generative Adversarial Networks (GANs) and its variants have ...