ntousis, odysseas makris, evangelos tsanakas, panayiotis pavlatos, christos
UAVs are widely used for multiple tasks, which in many cases require autonomous processing and decision making. This autonomous function often requires significant computational capabilities that cannot be integrated into the UAV due to weight or cost limitations, making the distribution of the workload and the combination of the results produced n...
lala, timotei
In this paper, the theoretical stability of batch offline action-dependent heuristic dynamic programming (BOADHDP) is analyzed for deep neural network (NN) approximators for both the action value function and controller which are iteratively improved using collected experiences from the environment. Our findings extend previous research on the stab...
halchenko, volodymyr y. trembovetska, ruslana tychkov, volodymyr kovtun, viacheslav tychkova, nataliia
A number of computer experiments have investigated the effectiveness in terms of accuracy of the method for simultaneously determining the distributions of electrical conductivity and magnetic permeability in the subsurface zone of planar conductive objects when modeling the process of eddy-current measurement testing by surface probes. The method ...
ervik, øyvind rødde, mia hofstad, erlend fagertun tveten, ingrid langø, thomas leira, håkon o. amundsen, tore sorger, hanne
Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a cornerstone in minimally invasive thoracic lymph node sampling. In lung cancer staging, precise assessment of lymph node position is crucial for clinical decision-making. This study aimed to demonstrate a new deep learning method to classify thoracic lymph nodes based...
haiyang, li xiaozhi, qi ying, hu zhang, jianwei
Glioblastoma, a highly aggressive brain tumor, is challenging to diagnose and treat due to its variable appearance and invasiveness. Traditional segmentation methods are often limited by inter-observer variability and the lack of annotated datasets. Addressing these challenges, this study introduces Arouse-Net, a 3D convolutional neural network tha...
di barba, paolo ghafoorinejad, arash mognaschi, maria evelina dughiero, fabrizio forzan, michele sieni, elisabetta
In this paper, a multi-physics case study belonging to the class of induction heating problem is considered. Finite Element Analysis is used to evaluate the temperature along a line on a graphite disk heated by two power inductors. In order to build a surrogate field model of the device, i.e., to compute the temperature profile on the disk, given t...
man, lu peixin, ye
We introduce the Hölder width, which measures the best error performance of some recent nonlinear approximation methods, such as deep neural network approximation. Then, we investigate the relationship between Hölder widths and other widths, showing that some Hölder widths are essentially smaller than n-Kolmogorov widths and linear widths. We also ...
Popli, Nipun Davoodi, Elnaz Capitanescu, Florin Wehenkel, Louis
peer reviewed / In this paper, we focus on the robustness of machine learning based proxies used to speed up, alone or jointly with state-of-the-art mathematical optimization methods, optimal power flow and security-constrained optimal power flow calculations. On data sets for the Nordic32 alternative current security-constrained optimal power flow...
akter, asrafi lee, myungho
Image inpainting for indoor environments presents unique challenges due to complex spatial relationships, diverse lighting conditions, and domain-specific object configurations. This paper introduces a resource-efficient post-processing framework that enhances domain-specific image inpainting through an adaptation mechanism. Our architecture integr...
colonnese, federica di luzio, francesco rosato, antonello panella, massimo
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by differences in social communication and repetitive behaviors, often associated with atypical visual attention patterns. In this paper, the Gaze-Based Autism Classifier (GBAC) is proposed, which is a Deep Neural Network model that leverages both data distillation and d...
