Výsledky vyhledávání - "Gambaruto, A. M."

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RBF-PINN: Non-Fourier Positional Embedding in Physics-Informed Neural Networks

Autor: Zeng, Chengxi, Burghardt, Tilo, Gambaruto, Alberto M

While many recent Physics-Informed Neural Networks (PINNs) variants have had considerable success in solving Partial Differential Equations, the empirical benefits of feature mapping drawn from the broader Neural Representations research have been la

Externí odkaz: http://arxiv.org/abs/2402.08367

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Feature Mapping in Physics-Informed Neural Networks (PINNs)

Autor: Zeng, Chengxi, Burghardt, Tilo, Gambaruto, Alberto M

In this paper, the training dynamics of PINNs with a feature mapping layer via the limiting Conjugate Kernel and Neural Tangent Kernel is investigated, shedding light on the convergence of PINNs; Although the commonly used Fourier-based feature mappi

Externí odkaz: http://arxiv.org/abs/2402.06955

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Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation

Autor: Zeng, Chengxi, Yang, Xinyu, Smithard, David, Mirmehdi, Majid, Gambaruto, Alberto M, Burghardt, Tilo

This paper presents a deep learning framework for medical video segmentation. Convolution neural network (CNN) and transformer-based methods have achieved great milestones in medical image segmentation tasks due to their incredible semantic feature e

Externí odkaz: http://arxiv.org/abs/2302.11325

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Video-TransUNet: Temporally Blended Vision Transformer for CT VFSS Instance Segmentation

Autor: Zeng, Chengxi, Yang, Xinyu, Mirmehdi, Majid, Gambaruto, Alberto M, Burghardt, Tilo

We propose Video-TransUNet, a deep architecture for instance segmentation in medical CT videos constructed by integrating temporal feature blending into the TransUNet deep learning framework. In particular, our approach amalgamates strong frame repre

Externí odkaz: http://arxiv.org/abs/2208.08315

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