Search Results - deep+learning

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Methods for real-time wideband RF waveform and emission classification
Revolutionary deep learning tech for accurate, real-time spectrum sensing of wireless signals like 5G, WiFi, and Bluetooth Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-17.jpg Background: Spectrum sensing is crucial in wireless communications for efficiently utilizing the limited available...
Published: 9/10/2024   |   Inventor(s): Tommaso Melodia, Milin Zhang, Salvatore D'Oro, Daniel Uvaydov, Francesco Restuccia, Clifton Robinson
Keywords(s): Deep learning, O-RAN, Spectrum sensing
Category(s): Technology Classifications > 3. Computer Science
SEM-O-RAN: Semantic NextG O-RAN Slicing for Data-Driven Edge-Assisted Mobile Applications
SEM-O-RAN uses O-RAN architecture and semantic compression to offload ML tasks to the edge, optimizing network resources and reducing latency. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-16.jpg Background The exponential growth in the number of connected devices and the increasingly...
Published: 9/10/2024   |   Inventor(s): Corrado Puligheddu, Francesco Restuccia, Carla Fabiana Chiasserini
Keywords(s): 5G and beyond, 5G Networks, 6G, Deep learning, Machine Learning, Mobile devices, O-RAN, Semantics, Software-defined Networks
Category(s): Technology Classifications > 3. Computer Science
SplitBeam: Rethinking Beamforming Feedback in MU-MIMO Wi-Fi Systems Through Split Neural Networks
SplitBeam uses a split deep neural network to optimize Wi-Fi beamforming, improving connectivity and reducing interference by processing the channel state information matrix with machine learning. Copy Image URL via instructions below https://nu.testtechnologypublisher.com/files/sites/mark-saulich-9.jpg Background: Contemporary Wi-Fi networks...
Published: 9/10/2024   |   Inventor(s): Niloofar Bahadori, Francesco Restuccia, Marco Levorato, Yoshitomo Matsubara
Keywords(s): Deep learning, MU-MIMO, Split Computing, Wi-Fi
Category(s): Technology Classifications > 3. Computer Science
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: 7/23/2024   |   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
Full Spectrum Computer Vision for Photon Counting CT (Case No. 2024-058)
Summary: Researchers in the Department of Radiological Sciences have developed a machine learning algorithm that processes multispectral photon counting CT data for accurate medical imaging. Background: Photon counting computed tomography (PCCT) is a tremendous engineering advancement, enabling high resolution spectral imaging with myriad applications....
Published: 9/20/2024   |   Inventor(s): Matthew Brown, Dieter Enzmann, John Hoffman, Michael Mcnitt-Gray
Keywords(s): AI algorithms, Algorithm, Algorithm Optical Coherence Tomography, algorithmic cancer detection, Artifical Intelligence (Machine Learning, Data Mining), artificial electromagnetic materials, Artificial Intelligence, artificial intelligence augmentation, Artificial Neural Network, Artificial Neural Network Artificial Neuron, artificial-intelligent materials, Big Data, Bladder Cancer, blood cancers, Brain cancer, Breast Cancer, Cancer, cancer antigen, cancer detection, Cancer Immunotherapy, Cancer stem cells, cancer target, Computed tomography, CT, Deep Learning, design software, Digital Pathology, generative artificial intelligence, Genetic Algorithm, Histopathological image analysis, Histopathology, histopathology images, hyperparameter optimization, Image Analysis, Image Processing, lympathic cancers, lymphatic cancer, Medical artificial intelligence (AI), Mesenchymal Stem Cell Derived Cancer Cells, Orthotopic cancer models, Pancreatic cancer, pathology image analysis, Photon counting computed tomography (PCCT), prostate cancer, Radiology, Radiology / Radiomitigation, Software, Software & Algorithms, Software Development Tools, Software-enabled learning
Category(s): Software & Algorithms, Software & Algorithms > Image Processing, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Data Analytics
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
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
A Deep-Learning Framework for Quantitative Magnetic Resonance Imaging (Case No. 2021-268)
Summary: Researchers from UCLA’s Departments of Bioengineering and Radiological Sciences have developed a novel deep learning framework for accelerated quantitative magnetic resonance imaging. Background: Fatty liver disease, or hepatic steatosis, affects nearly 2 billion people globally and has pernicious implications for deadlier diseases...
Published: 8/8/2024   |   Inventor(s): Holden Wu, Shu-Fu Shih
Keywords(s): Deep Learning, fat quantification, IIM framework, Imaging, Medical Imaging, Metabolic/Endocrinology, MRI, multiparametric MRI (mpMRI), radial MRI, uncertainty estimation
Category(s): Medical Devices, Medical Devices > Medical Imaging, Medical Devices > Medical Imaging > MRI, Electrical, Electrical > Imaging, Software & Algorithms
Convolutional Neural Networks for Organ Segmentation
Abstract: Accurate automated organ and disease feature segmentation is a challenge for medical imaging analysis. The pancreas, for example, is a small, soft, organ with low uniformity of shape and volume between patients. Because of the lack of uniform image patterns, there are few features that can be used to aid in automated identification of anatomy...
Published: 4/8/2024   |   Inventor(s): Holger Roth, Le Lu, Adam Harrison, Ronald Summers
Keywords(s): Computer Assisted Diagnostics, Computer Vision, Deep Learning, HNN, Holistically-Nested Convolutional Neural Network, Medical Imaging Informatics, National Institutes of Health Clinical Center, NIHCC
Category(s): Application > Software / Apps, Collaboration Sought > Licensing, Collaboration Sought > Collaboration
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