Abstract: Hyperspectral image classification methods based on subgraph neural networks (SGNNs) are rarely explored, and its advantage is that it can alleviate the neighbor explosion problem. After ...

Many studies have established that the attention mechanism has great potential in improving the performance of Convolutional Neural Networks (CNNs) in image classification problems in recent years.

You can find the complete code and data for this tutorial on my GitHub repository. If you prefer a quick overview, you can refer directly to the notebook, which contains all the code with concise ...

Learn how to download and process Sentinel-2 satellite imagery in just a few lines of code using the OpenEO Python client Sentinel-2 satellites are among the most widely used sources of Earth ...

Anomalous aortic origin of the coronary artery (AAOCA) is a rare cardiac condition that can cause ischemia or sudden cardiac death but might be overlooked or misclassified in routine coronary computed ...

Efficient extraction of spectral-spatial features is essential for accurate hyperspectral image (HSI) classification, where capturing both local texture and global semantic relationships is critical.

A new AI model, H-CAST, groups fine details into object-level concepts as attention moves from lower to high layers, outputting a classification tree—such as bird, eagle, bald eagle—rather than ...

Abstract: Auroral image classification has long been a focus of research in auroral physics. However, current methods for automatic auroral classification typically assume that only one type of aurora ...

Image classification is one of AI's most common tasks, where a system is required to recognize an object from a given image. Yet real life requires us to recognize not a single standalone object but ...

From spines on neurons to pollen on an insect’s eye, the winners of Nikon’s Small World photo contest offer a kaleidoscopic glimpse into a tiny world. These water fleas (Daphnia sp.) can reproduce ...

git clone [email protected]:facebookresearch/meru.git cd meru conda create -n meru python=3.9 --yes conda activate meru Install torch and torchvision following the instructions on pytorch.org. Then ...