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 ...

This paper proposes a human pose estimation network to enhance the detection accuracy of human body keypoints. The network initially divides the input image into four sub-regions. Subsequently, these ...

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 ...

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

What happens when you leave depression untreated? The symptoms may start small, then escalate, and affect your life and health. Learn more.