The proposed diffractive deep neural network employs orbital angular momentum encoding and diffractive layers to process spatial information from handwritten digits, offering a robust and versatile ...

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...

Object recognition through random scattering media has been an important but challenging task in many fields, such as biomedical imaging, oceanography, security, robotics, and autonomous driving.

Convolutional neural networks show remarkable results in classification but struggle with learning new things on the fly. We present a novel rehearsal-free approach, where a deep neural network is ...

Stellantis has been granted a patent for an object detection and classification verification system for vehicles. The system uses a projection system to project pre-captured 3D scenes onto a surface ...

A lot of science is about classification, but sometimes you encounter things that push the limits of those categories, displaying multiple distinctive characteristics at once. This is the case of Z ...

SAN FRANCISCO--(BUSINESS WIRE)--Capella Space Corp., a leading provider of high-resolution synthetic aperture radar (SAR) imagery, today announced that SATIM, a global leader in automatic object ...