Abstract: Due to the excellent feature extraction capabilities, deep learning has become the mainstream method for hyperspectral image (HSI ... multiscale transformer-based masked autoencoder ...

Abstract: As one of the fundamental research topics in remote sensing image analysis ... named compact and discriminative stacked autoencoder (CDSAE), for HSI classification. The proposed CDSAE ...

From carved stone to reinforced concrete, from raw timber to high-performance composites, each new material has expanded the structural, aesthetic, and functional boundaries of architecture.

While some argue that deep learning can reliably provide fine-grained classification and infer broader categories, this tactic only works with clear images. "Real-world applications involve plenty of ...

This repository will soon contain the code for our paper "ClimSat - A Diffusion Autoencoder Model for Climate-conditional Satellite Image Editing" published ... i.e., data augmentation for land cover ...

This project demonstrates a complete machine learning pipeline including data preprocessing, model design, training, evaluation, and analysis. It implements multiple CNN architectures with systematic ...

Patients and endoscopic images were labeled as either pCR or non-pCR based on postoperative pathology results. We systematically evaluated mainstream AI models and proposed EC-HAENet, a ...