Comparison of inference speed using TensorFlow (available as standard on Fugaku) and using “SoftNeuro” optimized for Fugaku.\n[Measured Values]Average elapsed time Using \"SoftNeuro\" optimized for \"Fugaku\": approx.\n19.2 times faster (*1) Inference Engine Inference Time (ms) TensorFlow 2820 “SoftNeuro” 147Average power consumption Using \"SoftNeuro\" optimized for \"Fugaku\": approx.\nMorpho will support further acceleration of 3D simulations (galaxy formation simulations) using deep learning on Fugaku through the project and collaboration.\nMorpho will provide broad support, making a wide range of innovations happen with its imaging technology and Deep Learning technology.
"}}}},{"node":{"postTitle":"LGBTQ: Aim to make it easier to change gender in Wales","slug":"lgbtq-aim-to-make-it-easier-to-change-gender-in-wales","publishDate":"None","createdLocal":"2023-02-09 14:31:03.845102","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"The Welsh government would also use \"all available powers to ban all aspects\" of so-called conversion therapy practices, which refers to any form of treatment or psychotherapy aiming to change a person's sexual orientation or to suppress a person's gender identity, and \"seek the devolution of any necessary additional powers\".
"}}}},{"node":{"postTitle":"Deep Learning Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2017-2027","slug":"deep-learning-market-global-industry-size-share-trends-opportunity-and-forecast-2017-2027","publishDate":"2023-02-08 00:00:00","createdLocal":"2023-02-09 14:31:02.764630","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"New York, Feb. 08, 2023 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report \"Deep Learning Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, 2017-2027\" - https://www.reportlinker.com/p06316219/?utm_source=GNWThe global deep learning market is expected to grow at an impressive CAGR in the forecast period, 2023-2027.\nDeep learning technology enhances the automation process, drives artificial intelligence applications, and services, and performs analytical and physical tasks without human intervention.\nThe advancements in deep learning technology and the growing use of advanced technologies in automobiles are expected to accelerate the global deep learning market growth for the next five years.\nMarket SegmentationThe global deep learning market is segmented into an offering, application, end-user industry, architecture, company, and regional distribution.Based on the offering, the market is divided into hardware, software, and services.\nReport Scope:In this report, the global deep learning market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:• Deep Learning Market, By Offering:o Hardwareo Softwareo Services• Deep Learning Market, By Application:o Image Recognitiono Signal Recognitiono Data Mining• Deep Learning Market, By End-User Industry:o Healthcareo Retailo Automotiveo Securityo Manufacturingo Others• Deep Learning Market, By Architecture:o RNNo CNNo DBNo DSNo GRU• Deep Learning Market, By Region:o North AmericaUnited StatesCanadaMexicoo Asia-PacificChinaIndiaJapanSouth KoreaAustraliaSingaporeMalaysiao EuropeGermanyUnited KingdomFranceItalySpainPolandDenmarko South AmericaBrazilArgentinaColombiaPeruChileo Middle East & AfricaSaudi ArabiaSouth AfricaUAEIraqTurkeyCompetitive LandscapeCompany Profiles: Detailed analysis of the major companies present in the global deep learning market.
"}}}},{"node":{"postTitle":"Automated machine learning recognition to diagnose flood resilience of railway switches and crossings","slug":"automated-machine-learning-recognition-to-diagnose-flood-resilience-of-railway-switches-and-crossings","publishDate":"None","createdLocal":"2023-02-09 14:31:01.961945","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"In addition, Table 1 includes the class for the classification of the machine learning model.\nFull size imageData preparation and machine learning model developmentThere are 1936 simulations in total.\nThe second one is the regression model when the machine learning model is developed to predict the current stiffness of railway turnout supports.\nThe concept of grid search is the machine learning model will try every combination that is defined by the grid search.\nFull size tableThe novelty of the developed machine learning model is the machine learning model in this study uses raw data or time-series data that previous studies have never done before.
"}}}},{"node":{"postTitle":"6 Things to Know About Computational Intelligence in Robotics Before Learning","slug":"6-things-to-know-about-computational-intelligence-in-robotics-before-learning","publishDate":"2023-02-08 00:00:00","createdLocal":"2023-02-09 14:30:59.742676","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"In this guide, let’s check out the six things you should know about computational intelligence in robotics before learning it!\nPrerequisites to Learning Computational Intelligence in RoboticsBefore learning computational intelligence in robotics, you’ll need to know the following.\nBenefits of Learning Computational Intelligence in RoboticsLearning computational intelligence in robots has many advantages, as stated.\nHow to Study Computational Intelligence In RoboticsYou can begin studying Computational Intelligence with a solid background in mathematics, especially probability, calculus, and linear algebra.\nFinal WordsIn conclusion, computational intelligence is a subset of artificial intelligence that simulates human intelligence using methods and algorithms to tackle challenging issues.
"}}}},{"node":{"postTitle":"Funding to restaurant and retail tech in Asia-Pacific expected to dip","slug":"funding-to-restaurant-and-retail-tech-in-asia-pacific-expected-to-dip","publishDate":"2023-02-08 13:39:31+00:00","createdLocal":"2023-02-09 14:30:57.422558","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"In-store retail and restaurant tech in the APAC region netted $1.1 billion dollars in 2021, a 45% jump from 2020 levels, according to AgFunder’s recent Asia-Pacific AgriFoodTech Investment Report.\nIn-store retail and restaurant tech emerged APAC’s fourth largest investment category, after eGrocery, Midstream Technologies and Restaurant Marketplaces.\nThe deal was the largest in this category globally and contributed nearly half of APAC’s total in-store retail and restaurant tech investments.\nTop countries in restaurant tech fundingTrax’s $640 million round bumped up Singapore’s overall venture capital flows, positioning the country at the top with $708.1 million.\nChina, well known for its advanced restaurant tech industry came in second with $155.6 million while Australia followed with $112.4 million.
"}}}},{"node":{"postTitle":"Connected Tire Market Is Expected To Reach around USD 45.60 Million by 2030, Grow at a CAGR Of 68.5% during Forecast Period 2023 To 2030 | Data By Contrive Datum Insights Pvt Ltd.","slug":"connected-tire-market-is-expected-to-reach-around-usd-45-60-million-by-2030-grow-at-a-cagr-of-68-5-during-forecast-period-2023-to-2030-data-by-contrive-datum-insights-pvt-ltd","publishDate":"None","createdLocal":"2023-02-09 14:30:57.363728","feedName":"Connected Car","postSummary":{"childMarkdownRemark":{"html":"Farmington, Feb. 08, 2023 (GLOBE NEWSWIRE) -- The Global Connected Tire Market Size Was Valued At USD 0.75 Million In 2021.\nThe Market Is Projected To Grow From USD 1.18 Million In 2022 To USD 45.60 Million By 2030, Exhibiting A CAGR Of 68.5% During The Forecast Period.\nOur research shows that the global market was 18.0% smaller in 2020 than in 2019.\nRequest Sample Copy of Report “ Connected Tire Market - Global Industry Analysis, Size, Share, Growth Opportunities, Future Trends, Covid-19 Impact, SWOT Analysis, Competition and Forecasts 2022 to 2030 ”, published by Contrive Datum Insights.\nThis could make the market grow less quickly.
"}}}},{"node":{"postTitle":"Move surveillance to a proactive security strategy with video analytics","slug":"move-surveillance-to-a-proactive-security-strategy-with-video-analytics","publishDate":"None","createdLocal":"2023-02-09 14:30:55.943663","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"Video analytics deliver new levels of video intelligence to autonomously detect, analyze and report events of interest as they are developing.\nHowever, it’s important for security leaders to keep in mind that all video analytics are not the same.\nNext-generation video analytics is video understandingBehavioral analytics recognize the behavior of diverse objects and their relevant actions and context.\nBehavioral analytics can do this by learning from video clips to create a unique signature for the behavior in the clip.\nThe success of established and future deployments will only serve to further accelerate the deployment of advanced behavioral recognition video analytics, transforming traditional reactive video systems into proactive sources of video data and intelligence.
"}}}}]}},"pageContext":{"limit":8,"skip":6168,"homeNumPages":1077,"currentPage":772}}}