The purpose of filters’ inverse modeling is to acquire the values of physical or geometrical parameters for the specified electrical response. In this article, a dimensionality reduction (DR) strategy ...

Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

The study’s authors note that small neural networks — simplified versions of the neural networks typically used in commercial ...

Google said in the coming months educators will be able to assign Gems and notebooks grounded in class materials directly to students through Google Classroom through new teacher-led experiences. With ...

Modeling of gas–solid, heterogeneously catalytic, diameter-transformed fluidized bed (DTFB) reactors is intrinsically complex and requires considering the variation of material properties and ...

Researchers at Osnabrück University, Freie Universität Berlin and other institutes recently developed a new class of artificial neural networks (ANNs) that could mimic the human visual system better ...

Imagine a computer that does not rely only on electronics but uses light to perform tasks faster and more efficiently. A collaboration between two research teams from Tampere University in Finland and ...

This framework could then be integrated with existing neuroscience theories. To develop their framework, they employed artificial neural networks (ANNs) trained via reinforcement learning.

Anomaly detection is a critical issue across several academic fields and real-world applications. Artificial neural networks have been proposed to detect anomalies from different input types, but ...