The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...
Introduction: Hepatocellular carcinoma (HCC), a predominant subtype of liver cancer, remains Q7 a major contributor to global cancer mortality. Accurate delineation of liver tumors in CT and MRI scans ...
Neural networks are designed to learn compressed representations of high-dimensional data, and autoencoders (AEs) are a widely-used example of such models. These systems employ an encoder-decoder ...
Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant improvements in classification accuracy. However, most current hyperspectral ...
Abstract: The ionosphere is vital for satellite navigation and radio communication, but observational limitations necessitate ionospheric forecasting. The least squares collocation (LSC) method is ...
Abstract: This study presents a deep learning (DL)-based approach to the seismic velocity inversion problem, focusing on both noisy and noiseless training datasets of varying sizes. Our seismic ...
The landscape of vision model pre-training has undergone significant evolution, especially with the rise of Large Language Models (LLMs). Traditionally, vision models operated within fixed, predefined ...