The design of metasurface-based devices with high-accuracy functionalities is significantly desirable. Towards this goal, Scientist in China propose a bidirectional deep neural network combined ...

Training algorithm breaks barriers to deep physical neural networks Date: December 7, 2023 Source: Ecole Polytechnique Fédérale de Lausanne Summary: Researchers have developed an algorithm to ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

Using this information, the model can then tell us the probability of a drug-protein interaction that we did not previously have in the database, as the algorithms can efficiently analyse large ...

The chip design used in the experiments was the latest version of Google’s Tensor Processing Unit (TPU), which is designed to run exactly the same sort of neural network algorithms for use in ...

Researchers at Soongsil University (Korea) published “A Survey on Efficient Convolutional Neural Networks and Hardware Acceleration.” Abstract: “Over the past decade, deep-learning-based ...

By using a neural network-based decoupling algorithm, the team was able to resolve spectral interference within the existing system, reducing both the complexity and cost of the design.