Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
Wolfram-like attention framing meets spiking networks: event-triggered, energy-thrifty AI that “wakes” to stimuli.
MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively launches a quantum-enhanced deep convolutional neural network image 3D reconstruction ...
Deep learning driven reconstruction of acoustic logging signal in energy exploration and development
In oil and gas exploration and development, logging curves are the key data for obtaining underground geological information. However, in actual acquisition processes, problems such as drilling fluid ...
ABSTRACT: Predicting the progression from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) is a critical challenge for enabling early intervention and improving patient outcomes. While ...
Abstract: This paper proposes a predictive regression model based on Convolutional Neural Networks(CNN) for predicting the magnetic field peaks of periodic magnetic systems under different periods ...
Neural processing unts (NPUs) are the latest chips you might find in smartphones and laptops — but what are they ard why are they so important? When you purchase through links on our site, we may earn ...
Digital tools and non-destructive monitoring techniques are crucial for real-time evaluations of crop output and health in sustainable agriculture, particularly for precise above-ground biomass (AGB) ...
Abstract: Convolutional neural networks (CNNs) are effective tools for regression tasks. However, their black-box nature limits their applicability in high-impact and high-risk tasks. In this paper, a ...
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