GPU-Accelerated Feature Extraction for Real-Time Vision AI and LLM Systems Efficiency: Autonomous Image Segmentation, Unsupervised Clustering, and Smart Pattern Recognition for Scalable AI Processing with 6.6× Faster Performance, 2.5× Higher Accuracy, and UX-Centric UI Boosting Human-in-the-Loop Productivity

The high computational cost of digital image processing, requiring high-performance hardware and extensive resources, severely limits real-time applications. While advancements in algorithm design and GPU acceleration have significantly improved efficiency, modern AI-driven applications such as larg...

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Vydáno v:	ASMC proceedings s. 1 - 8
Hlavní autoři:	Ahi, Kiarash, Wu, Stewart, Sriram, Satya, Fenger, Germain
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 05.05.2025
Témata:	Accuracy AI clustering Anomaly detection Artificial intelligence autonomous image segmentation Clustering algorithms Computational efficiency deep pattern recognition edge deployment Feature extraction GenAI Generative AI GPU-accelerated computing Image edge detection LLM Efficiency real-time AI inference Real-time systems Runtime scalable vision systems Tuning
ISSN:	2376-6697
On-line přístup:	Získat plný text
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