The human visual system provides us with a rich and meaningful percept of the world, transforming retinal signals into visuo-semantic representations. For a model of these representations, here we ...
(NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that they are actively exploring a shallow hybrid quantum-classical ...
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 ...
Abstract: With the rise of large language models in natural language processing, the use of various generative large language models for entity recognition has become a cutting-edge research approach.
Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...
ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
ABSTRACT: With the development of unmanned aerial vehicle (UAV) LiDAR technology, large-scale high-precision point cloud data is gradually playing an important role in the classification and ...
Advances in deep learning methods have demonstrated remarkable progress in wheelset fault diagnosis. However, current deep neural networks suffer from design flaws, including low accuracy, high ...
We compared human brain recordings during natural sound listening to representations within an artificial (deep) neural network (DNN) designed to categorize sounds. Despite not being exposed to real ...
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