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 ...
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 ...
Scientific Research Publishing

Organoid Intelligence: Bridging the Gap Between Biological and Artificial Neural Networks ()

Organoid Intelligence (OI) represents a groundbreaking convergence of biology and technology, aiming to redefine biocomputing using brain organoids—three-dimensional neural structures derived from ...
Morning Overview on MSN

New AI reads routine chest X-rays for early aging clues

Routine chest X-rays are quietly turning into a powerful new biomarker, as artificial intelligence learns to read subtle ...
eLife

Voltage imaging reveals the emergence of population activity in the spinal cord

This paper presents an important advance in genetically encoded voltage imaging of the developing zebrafish spinal cord in vivo, capturing voltage dynamics in neuronal populations, single cells, and ...
IEEE

RMSO-ConvNeXt: A Lightweight CNN Network for Robust SAR and Optical Image Matching Under Strong Noise Interference

Abstract: Synthetic aperture radar (SAR) and optical images provide complementary imaging information, and their joint application holds broad prospects in military reconnaissance and aircraft visual ...
IEEE

Adaptive Output Feedback Control Using Lyapunov-Based Deep Recurrent Neural Networks (Lb-DRNNs)

Abstract: Unlike traditional feedforward neural networks, recurrent neural networks (RNNs) possess a recurrent connection that allows them to retain past information. This internal memory enables RNNs ...