Search Results - deep+learning

3 Results

Sort By:

Facial Recognition Based on Converted Spiking Neural Network

Reference #: 01602 The University of South Carolina is offering licensing opportunities for Facial Recognition Based on Converted Spiking Neural Network Background: The current method for facial recognition requires a lot of computing resources (high-performance computers) which is not portable, and the accuracy is very limited. Invention Description: We...

Published: 10/17/2024 | Inventor(s): Yu Qian, Youzhi Tang

Keywords(s): deep learning, Facial recognition, mobile computing, Spiking neural networks

Category(s): Software and Computing

Projection System for Visual Morphing of Patient Disease

Reference #: 01430 The University of South Carolina is offering licensing opportunities for Projection System for Visual Morphing of Patient Disease Background: Many patients fail to truly understand the implications of their condition. They sometimes neglect how their disease can progress and thus do not prioritize their medications and needed lifestyle...

Published: 12/20/2022 | Inventor(s): Richard Hoppmann, Steven Wilson, Robert (Toufic) Haddad, Floyd Bell

Keywords(s): age-progression, AI, artificial intelligence, deep learning, disease-progression, education, educational device, Medical images, morphing, pathology, predictions, real-time

Category(s): Health Sciences, Software and Computing

Computer Vision Based Real-Time Pixel-Level Railroad Track Components Detection System

Reference #: 01467 The University of South Carolina is offering licensing opportunities for Computer vision based real-time pixel-level railroad track components detection system Background: Rail inspection is the practice of examining railroads for flaws that could lead to catastrophic failures. This process takes a lot of time and is typically...

Published: 9/3/2022 | Inventor(s): Yu Qian, Feng Guo

Keywords(s): convolutional neural network, deep learning, image analysis, missing or broken component, railroad track inspection, real-time process

Category(s): Software and Computing, Engineering and Physical Sciences