Abstract: In recent years, neural network models have been widely used in many tasks, however, tampering operations from malicious attackers, e.g., backdoor attacks and parameter malicious tampering, ...

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

Take a closer look at both the landing page and dashboard of your next AI SaaS platform. These essential features are designed to enhance your experience and are included at no extra cost with your ...

The ability to analyze the brain's neural connectivity is emerging as a key foundation for brain-computer interface (BCI) technologies, such as controlling artificial limbs and enhancing human ...

Abstract: This study investigates the application of Spiking Neural Network (SNN) in seismic signal denoising by developing a Convolutional Neural Network (CNN) to SNN conversion framework. We focus ...

Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China Department of Physics, City University of Hong Kong, Kowloon 999077, Hong Kong China ...

3D rendering—the process of converting three-dimensional models into two-dimensional images—is a foundational technology in computer graphics, widely used across gaming, film, virtual reality, and ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...

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 ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...