The semantic segmentation of remote sensing (RS) image is a hot research field. With the development of deep learning, the semantic segmentation based on a full convolution neural network greatly ...

In this paper, we propose an end-to-end trainable Convolutional Neural Network (CNN) architecture called the M-net, for segmenting deep (human) brain structures from Magnetic Resonance Images (MRI). A ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Researchers have uncovered how primate brains transform flat, 2D visual inputs into rich, 3D mental representations of ...

A study published in npj Computational Materials presents a new AI system that uses computer vision and language processing ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

Yale researchers have discovered a process in the primate brain that sheds new light on how visual systems work and could ...

This useful study presents a biologically realistic, large-scale cortical model of the rat's non-barrel somatosensory cortex, investigating synaptic plasticity of excitatory connections under varying ...

Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like telling a leaf apart from a rock. But they have struggled to build ...

GREmLN leverages a graph-based architecture to represent gene-gene interactions to predict cell behavior for therapeutic ...

Scientists have developed a new 2D superlattice that boosts the structural stability of zinc-ion battery cathodes, allowing the battery to operate reliably for over 5,000 charge-discharge cycles.