Part-Aware Correlation Networks for Few-shot Learning
Few-shot learning brings the machine close to human thinking which enables fast learning
with limited samples. Recent work considers local features to achieve contextual semantic …
with limited samples. Recent work considers local features to achieve contextual semantic …
Adaptive transfer learning-based cryptanalysis on double random phase encoding
Encrypting data can convert original data into a form that cannot be recognized and conceal
personal information. To ensure data security, analyzing cryptographic algorithms used in …
personal information. To ensure data security, analyzing cryptographic algorithms used in …
An Hybridization Method of Clustering Images Using Artificial Ants Model (CLAntIMG)
Image clustering is an unsupervised learning task that primary function is to categorise and
extract the image's valuable attributes. Many techniques like data augmentation and …
extract the image's valuable attributes. Many techniques like data augmentation and …
seUNet-Attention Based COVID-19 Lung Infection Segmentation Model
Y Bi, T Zhang, J Chang, J Wang, X Lu… - 2024 IEEE 3rd …, 2024 - ieeexplore.ieee.org
This paper addresses the challenge of accurately segmenting COVID-19 lung infections in
CT images, crucial for disease diagnosis and treatment. It proposes an improved seUNet …
CT images, crucial for disease diagnosis and treatment. It proposes an improved seUNet …