Search Results - artificial+intelligence+algorithms

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Monitoring Structural Health Using Diffractive Optical Processors (Case No. 2025-201)

Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel structural health monitoring system that is highly accurate and cost effective, addressing limitations in current infrastructure and civil health monitoring and a rise in public safety concerns. Background: The need for structural health monitoring...

Published: 6/25/2025 | Inventor(s): Aydogan Ozcan, Ertugrul Taciroglu, Yuntian Wang, Yuhang Li

Keywords(s): 3D structures, Adaptive Optics, AI-generated images and content, all-optical diffractive computing, all-optical transformation, analog computing, analog optical computing, Analogue Electronics, Artifical Intelligence (Machine Learning, Data Mining), Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial-intelligent materials, civil engineering, civil infrastructure, civil monitoring, computational imaging, computational imaging task, Construction, deep diffractive network, Diffraction, diffractive design, diffractive image reconstruction, diffractive network, diffractive processor, diffractive surface, digital image reconstruction, electromagnetic spectrum, Electro-Optics, Image Analysis, Image Processing, Image Resolution, image restoration, image signal processing, Imaging, Infrastructure, Lens (Optics), linear optics, Nanostructure, optical processor, optically-guided structural monitoring, Optics, passive light-matter interactions, security imaging, Signal Reconstruction, Structural health monitoring, structural health monitoring (SHM), structure monitoring, Structures

Category(s): Electrical, Electrical > Signal Processing, Electrical > Imaging, Materials, Materials > Construction Materials, Electrical > Visual Computing, Electrical > Computing Hardware, Electrical > Instrumentation, Energy & Environment, Energy & Environment > Energy Efficiency, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Image Processing, Software & Algorithms > Programs

Batch Processing for Imaris Stitcher (Case No. 2025-089)

Summary: Researchers in UCLA’s Department of Neurobiology have developed a novel software tool that enhances the capabilities of Imaris Stitcher. The tool enables batch processing and automated execution of multiple image stitching jobs, significantly improving workflow efficiency and reducing hands-on time. This results in readily available,...

Published: 5/13/2025 | Inventor(s): Ian Bowman, Mitchell Rudd, Hong Wei Dong

Keywords(s): 3D tissue imaging, 3D ultrasound imaging, Artifical Intelligence (Machine Learning, Data Mining), Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial-intelligent materials, bioimaging, Cell Counting/Imaging, cell imaging, cell mapping, computational imaging, Data Acquisition, Data Aggregator, Data Analytics, Data Recovery, Data Structure, Fluorescence Microscope, histopathology images, Image Analysis, image restoration, image signal processing, Imaging, Magnetic Resonance Imaging, Medical artificial intelligence (AI), Medical Imaging, Microscope, Microscopy, Microscopy And Imaging, Molecular Imaging, multi-contrast imaging, Neuroimaging, non-invasive imaging, pathology image analysis, Phase-Contrast Imaging, three dimensional imaging, volumetric image

Category(s): Software & Algorithms, Software & Algorithms > AI Algorithms, Software & Algorithms > Digital Health, Software & Algorithms > Image Processing

Event-Driven Integrate and Fire (EIF) Neuron Circuit for Neuromorphic Computing System (Case No. 2024-275)

Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed an energy efficient neuromorphic computing architecture. Background: Widespread growth in demand for artificial intelligence systems has highlighted limitations in current central processing unit (CPU) designs, particularly in terms of energy efficiency...

Published: 3/4/2025 | Inventor(s): Mau-Chung Chang, Chao Jen Tien, Yong Hei

Keywords(s): Advanced Computing / AI, advanced computing methods, AI hardware, analog computing, Artifical Intelligence (Machine Learning, Data Mining), artificial electromagnetic materials, Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, artificial intelligence-generated content, Artificial Neural Network, Artificial Neural Network Artificial Neuron, artificial presenting cells, artificial-intelligent materials, Cloud Computing, computational efficiency, computational imaging, compute-in-memory, Computer Aided Learning, Computer Architecture, Computer Monitor, Computer Vision, CPU design, deep neural networks (DNN), Energy Density, Energy Efficiency, event-driven processing, generative artificial intelligence, latency encoding, low latency computing, low-power architecture, matrix multiplication, Medical artificial intelligence (AI), Neuromorphic computing, offline learning, online learning, spike neural networks (SNN), Supercomputer

Category(s): Electrical, Electrical > Signal Processing, Electrical > Electronics & Semiconductors, Electrical > Computing Hardware, Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning

Intraoperative Deep Learning Model for Imputation of the Continuous Central Venous Pressure (CVP) and Pulmonary Arterial Pressure (PAP) Waveforms From (Case No. 2024-224)

Summary: Researchers in the UCLA Department of Anesthesiology have developed a deep learning model to accurately represent and visualize hemodynamic waveforms, or blood flow patterns, with minimally invasive approaches. Background: Swan-Ganz (SG) catheters are used for precise cardiac hemodynamic evaluations. Indicated for patients with severe...

Published: 2/14/2025 | Inventor(s): Maxime Cannesson, Sungsoo Kim, Akos Rudas, Jeffrey Chiang, Ravi Pal

Keywords(s): active learning, Algorithm, algorithm-based testing, arterial blood pressure (ABP), Artifical Intelligence (Machine Learning, Data Mining), artificial intelligence algorithms, blood cancers, blood flow management, Blood Pressure, Blood Proteins, cardiovascular monitoring, catheter, Catheterization, central venous pressure (CVP), Computer Aided Learning, Continuous blood pressure monitoring, critical care, curriculum learning, Deep Learning, Deep learning-based sensing, deep-learning analysis algorithms, heart failure, hemodynamic monitoring, Machine Learning, non-invasive monitoring, Perceptual Learning, pulmonary arterial pressure (PAP), Software & Algorithms, Swan-Ganz catheter

Category(s): Software & Algorithms, Software & Algorithms > Digital Health, Software & Algorithms > Artificial Intelligence & Machine Learning, Medical Devices, Medical Devices > Monitoring And Recording Systems