|
|
|
|
|
Juan Murillo-Morera, Carlos Castro-Herrera, Javier Arroyo, Ruben Fuentes-Fernandez
Pág. 114 - 137
Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding so...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nils Hütten, Miguel Alves Gomes, Florian Hölken, Karlo Andricevic, Richard Meyes and Tobias Meisen
Quality assessment in industrial applications is often carried out through visual inspection, usually performed or supported by human domain experts. However, the manual visual inspection of processes and products is error-prone and expensive. It is ther...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dilip Kumar Roy, Mohamed Anower Hossain, Mohamed Panjarul Haque, Abed Alataway, Ahmed Z. Dewidar and Mohamed A. Mattar
This study addresses the crucial role of temperature forecasting, particularly in agricultural contexts, where daily maximum (????????
T
m
a
x
) and minimum (????????
T
m
i
n
) temperatures significantly impact crop growth and irrigation planning. While ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Bata Hena, Ziang Wei, Luc Perron, Clemente Ibarra Castanedo and Xavier Maldague
Industrial radiography is a pivotal non-destructive testing (NDT) method that ensures quality and safety in a wide range of industrial sectors. Conventional human-based approaches, however, are prone to challenges in defect detection accuracy and efficie...
ver más
|
|
|
|
|
|
|
|
|
|
|
Gleice Kelly Barbosa Souza, Samara Oliveira Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos Oliveira, Daniela Carine Ramires Oliveira and Erivelton Geraldo Nepomuceno
Reinforcement learning is an important technique in various fields, particularly in automated machine learning for reinforcement learning (AutoRL). The integration of transfer learning (TL) with AutoRL in combinatorial optimization is an area that requir...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zimei Zhang, Jianwei Xiao, Wenjie Wang, Magdalena Zielinska, Shanyu Wang, Ziliang Liu and Zhian Zheng
Angelica sinensis (Oliv.) Diels, a member of the Umbelliferae family, is commonly known as Danggui (Angelica sinensis, AS). AS has the functions of blood tonic, menstrual pain relief, and laxatives. Accurate classification of AS grades is crucial for eff...
ver más
|
|
|
|
|
|
|
|
|
|
|
George Westergaard, Utku Erden, Omar Abdallah Mateo, Sullaiman Musah Lampo, Tahir Cetin Akinci and Oguzhan Topsakal
Automated Machine Learning (AutoML) tools are revolutionizing the field of machine learning by significantly reducing the need for deep computer science expertise. Designed to make ML more accessible, they enable users to build high-performing models wit...
ver más
|
|
|
|
|
|
|
|
|
|
|
Samuel de Oliveira, Oguzhan Topsakal and Onur Toker
Automated Machine Learning (AutoML) is a subdomain of machine learning that seeks to expand the usability of traditional machine learning methods to non-expert users by automating various tasks which normally require manual configuration. Prior benchmark...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tatyana Aksenovich and Vasiliy Selivanov
During geomagnetic storms, which are a result of solar wind?s interaction with the Earth?s magnetosphere, geomagnetically induced currents (GICs) begin to flow in the long, high-voltage electrical networks on the Earth?s surface. It causes a number of ne...
ver más
|
|
|
|
|
|