Abstract: In recent years, numerous designs have used systolic arrays to accelerate convolutional neural network (CNN) inference. In this work, we demonstrate that we can further speed up CNN ...

Abstract: To address the degradation in radiation performance caused by external deformations in variable-curvature cylindrical conformal antenna arrays, this letter proposes a real-time beam pattern ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Researchers used 3D printing and capillary action to create customizable neural chips, expanding design freedom for brain research, biosensors and biocomputing. (Nanowerk News) Cultured neural tissues ...

A new paper published in the journal Pharmaceutics sheds light on the growing role of 3D bioprinting in developing functional neural tissues. Their work assesses how emerging technologies can improve ...

A simulation model for the digital reconstruction of 3D root system architectures. Integrated with a simulation-based inference generative deep learning model.

Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...

ABSTRACT: With the advent of the 5G and future 6G, base stations will be used as station controllers. The antenna systems are networked and equipped with a processor to optimize the detection of ...