Utilizing machine learning to reduce cloud instances in a cloud computing environment .

Utilizing machine learning to reduce cloud instances in a cloud computing environment

Номер патента: US20220255795A1
Опубликовано: 11-08-2022
Автор(ы): Abhishek Kumar Singh, Nazia Sarang, Sunil Narang, Vikas Vijay
Принадлежит: Capital One Services LLC
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Рисунок 1. Взаимосвязь патентов (ближайшие 20).

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Blurring to improve visual quality in an area of interest in a frame

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Systems and methods for utilizing machine learning to minimize a potential of damage to fiber optic cables

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Systems and methods for utilizing machine learning to minimize a potential of damage to fiber optic cables

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Energy savings system based machine learning of wireless performance activity for mobile information handling system connected to plural wireless networks

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Energy savings system based machine learning of wireless performance activity for mobile information handling system connected to plural wireless networks

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Data Center Disaster Circuit Breaker Utilizing Machine Learning

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Method for optimizing the energy management of an aeronautical assembly to reduce greenhouse gas emissions and associated digital platform

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Improved entropy coding in image and video decompression using machine learning

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Wireless communications system, a radio network node, a machine learning unit and methods therein for transmission of a downlink signal in a wireless communications network supporting beam forming

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A wireless communications system, a radio network node, a machine learning unt and methods therein for transmission of a downlink signal in a wireless communications network supporting beamforming

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Wireless communications system, a radio network node, a machine learning unit and methods therein for transmission of a downlink signal in a wireless communications network supporting beam forming

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Systems and methods for firewall deployment in a transit virtual private cloud network deployed in a cloud computing environment

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Hybrid fiber cable distributed antenna system (hfc-das) network with machine learning beam

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Edge computing storage nodes based on location and activities for user data separate from cloud computing environments

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Utilizing machine learning and trusted transaction card locations to generate a geographical map of the trusted transaction cards

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Interactive graphical user interface for insurance claim handlers including identifying insurance claim risks and health utilizing machine learning

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Machine learning supplemented storage device inspections

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Generating forecasted emissions value modifications and monitoring for physical emissions sources utilizing machine-learning models

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Generating forecasted emissions value modifications and monitoring for physical emissions sources utilizing machine-learning models

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Machine learning models for diagnosis suspecting

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System and method for prediction analysis of a system utilizing machine learning networks

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Integrated machine learning training

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Collision analysis platform using machine learning to reduce generation of false collision outputs

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Hyper parameter tuning for machine learning models

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Aerial wildlife survey and wounded game animal tracking process for completing accurate aerial wildlife surveys by machine learning and AI-supported filtering of non-relevant information to count and report on specific targeted aspects of wildlife

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Container scheduling for executing dynamic workloads in cloud computing environments

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System and method utilizing machine learning to predict drop-off of user engagement with expert systems

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Automatically provisioning and managing secure database resources in a cloud computing environment

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Cloud-based fleet and asset management for edge computing of machine learning and artificial intelligence workloads

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Computing environment pooling

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Web application configuration settings for execution in a cloud computing environment

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System and method for in-place data writes to reduce fragmentation in a multidimensional database environment

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Methods and apparatus to generate code as a plug-in in a cloud computing environment

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Machine-learned component hybrid training and assistance of vehicle trajectory generation

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Use of machine learning techniques to enhance and accelerate inversion methods for the interpretation of deep directional resistivity measurements

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Methods of Analyzing Microscopy Images Using Machine Learning

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Elevator system management utilizing machine learning

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Machine learning based stabilizer for numerical methods

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Exploratory data analysis system for automated generation of search queries using machine learning techniques to identify certain log fields and correlation thereof

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