Search Results - deep+learning-based+sensing

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Deep Neural Networks for Real-Time Non-invasive Continuous Peripheral Oxygen Saturation Monitoring (Case No. 2024-227)

Summary: UCLA researchers in the Department of Anesthesiology have developed a novel pulse oximetry methodology utilizing deep neural networks for non-invasive monitoring. Background: In the US alone, over 5 million patients are admitted to the ICU for oxygen saturation monitoring. They, as well as the more than 15 million patients undergoing surgery,...

Published: 7/26/2024 | Inventor(s): Sungsoo (Danny) Kim, Sohee Kwon, Mia Markey, Alan Bovik, Akos Rudas, Ravi Pal, Maxime Cannesson

Keywords(s): Artifical Intelligence (Machine Learning, Data Mining), Blood Pressure, cardiovascular monitoring, central venous pressure (CVP), Continuous blood pressure monitoring, critical care, Deep learning-based sensing, deep-learning analysis algorithms, heart failure, hemodynamic monitoring, machine learning modeling, Monitoring (Medicine), neural network, non-invasive monitoring, Oxygen, Oxygen Saturation, pulmonary arterial pressure (PAP), Swan-Ganz catheter

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

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: 9/3/2024 | Inventor(s): Maxime Cannesson, Sungsoo (Danny) 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

Securing Camera and Photography Systems From Deepfakes by Verifying Provenance and Reducing Attack Surfaces (Case No. 2024-270)

Summary: Researchers in the UCLA Department of Electrical and Computer Engineering have developed a multi-layer security framework to verify deepfake imagery data. Background: The exponential improvements in generative AI pose serious implication to the rise of synthetic media or “deepfakes”. Soon, deepfake images and videos will be...

Published: 9/27/2024 | Inventor(s): Alexander Vilesov, Achuta Kadambi, Yuan Tian, Nader Sehatbakhsh

Keywords(s): AI image security, Artificial Intelligence, artificial intelligence algorithms, Artificial Neural Network, Artificial Neural Network Artificial Neuron, artificial-intelligent materials, attack surface reduction, data security, Deep Learning, Deep learning-based sensing, deep physical neural network, deepfake, deepfake protection, deep-learning analysis algorithms, deep-learning fake (deepfake), generative artificial intelligence, image authenticity verification, image provenance, image signal processing, Medical artificial intelligence (AI), social media, third-party verification

Category(s): Software & Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Image Processing, Software & Algorithms > Security & Privacy, Electrical, Electrical > Visual Computing, Electrical > Visual Computing > Video Processing

Universal Linear Intensity Transformations Using Spatially-Incoherent Diffractive Processors (Case No. 2023-192)

Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a novel platform technology to facilitate the design of all-optical visual processors, which can be used to perform advanced computational tasks at the speed of light. Background: Information processing via light is a cutting-edge field among optics...

Published: 4/5/2024 | Inventor(s): Aydogan Ozcan, MD Sadman Rahman, Xilin Yang

Keywords(s): Adaptive Optics, Algorithm Optical Coherence Tomography, all-optical diffractive computing, all-optical transformation, Artifical Intelligence (Machine Learning, Data Mining), Artificial Intelligence, Atomic Force Microscopy Optical Tweezers, computational imaging, deep diffractive network, Deep Learning, Deep learning-based sensing, diffractive processor, Dispersion (Optics), Electron Microscope, Electro-Optics, fluorescence microscopy, Focus (Optics), Infrared Electromagnetic Spectrum Dispersion (Optics), interference processor, large language model (LLNMs), linear optics, linear transformations, Machine Learning, Microscope, Microscopy, Microscopy And Imaging, Near-Field Scanning Optical Microscope, neural networks, Nonlinear Optics, non-linear optics, Optical Coherence , Optical Communication , Optical computing, Optical Fiber Copper Wire And Cable, optical implementation, Optical Microscope, Optical networks, optical processor, optical transmission, Optics Parabolic Reflector Curved Mirror, phase-only diffractive network, reverse engineered optical system, Software, Software & Algorithms, Software Development Tools, spatially-incoherent light, start to end optics design, Surgical Instrument Optical Coherence Tomography, three dimensional imaging, visual computing, Waferscale Processors

Category(s): Optics & Photonics, Optics & Photonics > Microscopy, Platforms, Software & Algorithms > Image Processing, Electrical, Electrical > Signal Processing, Electrical > Computing Hardware

Rapid Sensing of Hidden Objects and Defects Using a Single-Pixel Diffractive Terahertz Processor (Case No. 2023-184)

Summary: UCLA researchers have developed a diffractive sensor that leverages deep-learning-optimized diffractive layers to rapidly detect hidden objects and defects within a 3D sample without scanning or image processing. Background: Inspecting hidden structures is a critical requirement in various fields, including security, manufacturing, and...

Published: 6/13/2024 | Inventor(s): Aydogan Ozcan, Jingxi Li

Keywords(s): Deep learning-based sensing, Electrical, Electrical Engineering, Image Processing, Machine Learning, real-time sensing/monitoring/tracking, Remote Sensing, smart sensing, target detection

Category(s): Electrical, Electrical > Sensors, Optics & Photonics > Spectroscopy, Software & Algorithms > Artificial Intelligence & Machine Learning

Bio-Aerosol Detection Using Mobile Microscopy and Machine Learning (Case No. 2019-722)

Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed an air analysis instrument and accompanying virtual aerosol detection method that combines imaging and deep learning to sense and classify airborne particles without external labeling or post processing steps. Background: Air quality management, particularly...

Published: 11/7/2023 | Inventor(s): Aydogan Ozcan

Keywords(s): aerosol, Agricultural & plant biology research, air quality measurement, bioaerosol, Bioterrorism detection, Deep Learning, Deep learning-based sensing, Digital Holography, Holography, Indoor air quality monitoring, Industrial applications: food processing, fermentation, label-free sensing, pollen detection, real-time sensing/monitoring/tracking, smart sensing

Category(s): Software & Algorithms > Artificial Intelligence & Machine Learning, Life Science Research Tools > Microscopy And Imaging, Chemical > Chemical Sensors

Virtual Impactor-Based Label-Free Bio-Aerosol Detection Using Holography and Deep Learning (Case No. 2023-037)

Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed a virtual aerosol detection method that combines imaging and deep learning to sense and classify bio-aerosols without any external labeling or post processing steps. Background: Bio-aerosol detection and classification is pivotal to understanding and...

Published: 8/7/2024 | Inventor(s): Aydogan Ozcan, Yi Luo, Tairan Liu

Keywords(s): air quality measurement, Artificial Neural Network, bioterrorism, computational imaging, Deep learning-based sensing, Digital Electronics, Digital Holography, Digital Signal Processing, Imaging, label-free imaging, label-free sensing, Mass Spec, pollen detection, Sensors, virtual impactors

Category(s): Electrical, Electrical > Sensors, Electrical > Imaging, Life Science Research Tools, Life Science Research Tools > Mass Spectrometry