Introduction of artificial Intelligence
Artificial intelligence (AI) is referred to as the intelligence developed by machines with
mathematical modeling. In particular, AI is manifested by machine's ability to effectively …
mathematical modeling. In particular, AI is manifested by machine's ability to effectively …
Ischemic Stroke Segmentation by Transformer and Convolutional Neural Network Using Few-Shot Learning
F Alshehri, G Muhammad - ACM Transactions on Multimedia Computing …, 2024 - dl.acm.org
Stroke is a major factor in causing disability and fatalities. Doctors use computerized
tomography (CT) and magnetic resonance imaging (MRI) scans to assess the severity of a …
tomography (CT) and magnetic resonance imaging (MRI) scans to assess the severity of a …
Few Shot Learning for Medical Imaging: A Review of Categorized Images
Deep learning systems have advanced significantly in numerous medical applications,
improving various aspects of patient care. However, they still need to work on the issue of …
improving various aspects of patient care. However, they still need to work on the issue of …
ResDAC-Net: a novel pancreas segmentation model utilizing residual double asymmetric spatial kernels
The pancreas not only is situated in a complex abdominal background but is also
surrounded by other abdominal organs and adipose tissue, resulting in blurred organ …
surrounded by other abdominal organs and adipose tissue, resulting in blurred organ …
[PDF][PDF] Local image fitting-based active contour for vector-valued images
Variational active contour seeks to segment or extract desired object boundaries for further
analysis. The model can be divided into global segmentation and selective segmentation …
analysis. The model can be divided into global segmentation and selective segmentation …
Boosting Few-Shot Semantic Segmentation with Prior-Driven Edge Feature Enhancement Network
J Ma, S Bai, W Pan - IEEE Transactions on Artificial Intelligence, 2024 - ieeexplore.ieee.org
Few-shot Semantic Segmentation (FSS) focuses on segmenting objects of novel classes
with only a small number of annotated samples and has achieved great development …
with only a small number of annotated samples and has achieved great development …
Few-Shot Learning for Images Classification Considering Feature Variance
L Wang, M Xue, L Wang… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Few-shot learning aims to solve the problem of learning with limited samples. However,
existing metric-based meta-learning models have the issue of insufficient attention to feature …
existing metric-based meta-learning models have the issue of insufficient attention to feature …