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Ruoyang Li, Shuping Xiong, Yinchao Che, Lei Shi, Xinming Ma and Lei Xi
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentation ...
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Nirmal Acharya, Padmaja Kar, Mustafa Ally and Jeffrey Soar
Significant clinical overlap exists between mental health and substance use disorders, especially among women. The purpose of this research is to leverage an AutoML (Automated Machine Learning) interface to predict and distinguish co-occurring mental hea...
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Julia Figueroa-Martínez, Dulcenombre M. Saz-Navarro, Aurelio López-Fernández, Domingo S. Rodríguez-Baena and Francisco A. Gómez-Vela
Gene networks have become a powerful tool for the comprehensive examination of gene expression patterns. Thanks to these networks generated by means of inference algorithms, it is possible to study different biological processes and even identify new bio...
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Junlin Lou, Burak Yuksek, Gokhan Inalhan and Antonios Tsourdos
In this study, we consider the problem of motion planning for urban air mobility applications to generate a minimal snap trajectory and trajectory that cost minimal time to reach a goal location in the presence of dynamic geo-fences and uncertainties in ...
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Girolamo Musso, Iara Figueiras, Héléna Goubel, Afonso Gonçalves, Ana Laura Costa, Bruna Ferreira, Lara Azeitona, Simão Barata, Alain Souza, Frederico Afonso, Inês Ribeiro and Fernando Lau
The commercial space launch sector is currently undergoing a significant shift, with increasing competition and demand for launch services, as well as growing concerns about the environmental impact of rocket launches. To address these challenges, within...
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