Viral infections have long been a core focus in the field of public health. Antiviral peptides (AVPs), due to their unique mechanisms of action and significant inhibitory effects against a wide range ...

Background: Precise segmentation of hepatic neoplasms is essential for effective diagnosis and treatment planning. Manual segmentation of abdominal computed tomography (CT) images is time-intensive, ...

Adaptive Margin Contrastive Learning for Ambiguity-aware 3D Semantic Segmentation This repo is the official project repository of the papers: " AMContrast3D " and "AMContrast3D++".

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers ...

Contrastive learning tasks have received considerable attention within the SSL methods. Contrastive learning tasks aim to learn a latent space in which embeddings of similar data samples are pulled ...

We present a novel molecular property prediction framework that requires only the SMILES format as input but is designed to be multimodal by incorporating predicted 3D conformer representations. Our ...

Recently, pixel-to-pixel contrastive learning in single-scale feature space has been widely studied in semantic segmentation to learn a unified feature expression for pixels of the same category.

The transformer-based semantic segmentation approaches, which divide the image into different regions by sliding windows and model the relation inside each window, have achieved outstanding ...