Networks are systems comprised of two or more connected devices, biological organisms or other components, which typically ...
Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...
An Iterative Reconstruction Algorithm Based on Detail Transfer for Few-View Computed Tomography. Journal of Signal and ...
AI-powered biosensors can analyze intricate datasets from sensors in real time. Machine learning and deep learning algorithms ...
Spiking Neural Networks (SNNs) are a cutting-edge approach to artificial intelligence, designed to emulate the brain's architecture and functionality. Their ...
The MES system integrates genetic algorithms and particle swarm optimization mixed algorithms to capture over 10 types of ...
Artificial intelligence (AI) technologies are progressing rapidly, presenting opportunities and intricate ethical and legal issues. This evaluation delineates modern methodologies and classifications ...
A deep learning framework enhances personalized advertising by combining reinforcement learning, sentiment analysis, and user behavior ...
New research indicates that AI models can get smarter at seeing by solving jigsaw puzzles. Rearranging scrambled images, ...
This FAQ explores the fundamental architecture of neural networks, the two-phase learning process that optimizes millions of ...
Abstract: Dense convolutional network has been continuously refined to adopt a highly efficient and compact architecture, owing to its lightweight and efficient structure. However, as the current ...
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