Dynamic Neural Network Refinement (DNNR) is an advanced framework that allows neural networks to adapt in real time. Unlike static systems, DNNR refines network parameters on-the-fly to optimize performance. Its modularity ensures easy customization for versatile applications.
machine-learning deep-learning artificial-intelligence neural-networks intelligent-systems performance-optimization adaptive-systems machine-learning-framework data-driven-ai customizable-ai real-time-optimization ai-scalability on-the-fly-refinement network-parameter-tuning versatile-ai-solutions advanced-neural-architectures dynamic-learning-models ai-research-and-development
-
Updated
Sep 15, 2025 - Python