IEEE

TMAR: 3-D Transformer Network via Masked Autoencoder Regularization for Hyperspectral Sharpening

Abstract: Fusion-based hyperspectral super-resolution techniques are utilized to increase the spatial resolution of a hyperspectral image (HSI) by fusing it with a high spatial resolution assistive ...

How do AI coding agents work? We look under the hood.

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

Open-source software sheds light on cancer's hidden genetic networks

University of Navarra (Spain) researchers have developed RNACOREX, a new open-source software capable of identifying gene ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
IEEE

Online Public Opinion Situation Assessment by Deep Sparse Autoencoder and Time-Series Modeling Convolutional Neural Network

Abstract: We have developed an innovative framework for analyzing online public sentiment, referred to as the Online Public Opinion Situation Assessment (OPOSA) model. This model employs Deep Sparse ...