OpenPose-based motion analysis (OpenPose-MA), utilizing deep learning methods, has emerged as a compelling technique for estimating human motion. It addresses the drawbacks associated with conventional three-dimensional motion analysis (3D-MA) and hu...
Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic information, but some modalities are limited by the long scanning time. To accelerate the whole acquisition process, MRI reconstruction of one modality from highly under-sam...
Neural networks : the official journal of the International Neural Network Society
Aug 31, 2024
Vision Transformer have achieved impressive performance in image super-resolution. However, they suffer from low inference speed mainly because of the quadratic complexity of multi-head self-attention (MHSA), which is the key to learning long-range d...
Neural networks : the official journal of the International Neural Network Society
Aug 31, 2024
Single-channel speech enhancement primarily relies on deep learning models to recover clean speech signals from noise-contaminated speech. These models establish a mapping relationship between noisy and clean speech. However, considering the sparse d...
Neural networks : the official journal of the International Neural Network Society
Aug 31, 2024
Humans have the ability to constantly learn new knowledge. However, for artificial intelligence, trying to continuously learn new knowledge usually results in catastrophic forgetting, the existing regularization-based and dynamic structure-based appr...
Neural networks : the official journal of the International Neural Network Society
Aug 31, 2024
Selecting a set of initial users from a social network in order to maximize the envisaged number of influenced users is known as influence maximization (IM). Researchers have achieved significant advancements in the theoretical design and performance...
Delayed diagnosis and treatment resistance result in high pancreatic ductal adenocarcinoma (PDAC) mortality rates. Identifying molecular subtypes can improve treatment, but current methods are costly and time-consuming. In this study, deep learning m...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Aug 31, 2024
PURPOSE: To validate a CT-based deep learning (DL) hippocampal segmentation model trained on a single-institutional dataset and explore its utility for multi-institutional contour quality assurance (QA).
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