Apple’s upcoming iPhones and iPads will likely have much smaller notches than their predecessors thanks to a greatly reduced Face ID chip.\nThis is according to a report from Digitimes, which stated that the company has decided to scale down the die size of its VCSEL chips used in 3D Face ID sensors by 40-50%.\nDespite significant advancements in hardware and other design elements, Apple has stuck with the current notch since the iPhone X.\nThe image below shows the components contained within the iPhone’s notch.\nOther reports have suggested that Apple will release a new budget iPhone SE in 2023 which uses a hole-punch camera without Face ID support.
"}}}},{"node":{"postTitle":"Semantic Segmentation with TensorFlow Keras","slug":"semantic-segmentation-with-tensorflow-keras","publishDate":"2021-05-15 07:30:00+00:00","createdLocal":"2021-05-15 14:30:51.892788","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"In this article, we discuss semantic segmentation using TensorFlow Keras.\nAmong FCNNs, U-Net is one of the successful architectures acclaimed for its performance in Medical Image Segmentation.\ndef brightness(img, mask): img = tf.image.adjustbrightness(img, 0.1) return img, mask def gamma(img, mask): img = tf.image.adjustgamma(img, 0.1) return img, mask def hue(img, mask): img = tf.image.adjusthue(img, -0.1) return img, mask def crop(img, mask): img = tf.image.centralcrop(img, 0.7) img = tf.image.resize(img, (128,128)) mask = tf.image.centralcrop(mask, 0.7) mask = tf.image.resize(mask, (128,128)) mask = tf.cast(mask, tf.uint8) return img, mask def fliphori(img, mask): img = tf.image.flipleftright(img) mask = tf.image.flipleftright(mask) return img, mask def flipvert(img, mask): img = tf.image.flipupdown(img) mask = tf.image.flipupdown(mask) return img, mask def rotate(img, mask): img = tf.image.rot90(img) mask = tf.image.rot90(mask) return img, maskApply augmentation to the data with the above functions.\ntrain = tf.data.Dataset.zip((trainX, trainy)) val = tf.data.Dataset.zip((valX, valy)) # perform augmentation on train data only a = train.map(brightness) b = train.map(gamma) c = train.map(hue) d = train.map(crop) e = train.map(fliphori) f = train.map(flip_vert) g = train.map(rotate) train = train.concatenate(a) train = train.concatenate(b) train = train.concatenate(c) train = train.concatenate(d) train = train.concatenate(e) train = train.concatenate(f) train = train.concatenate(g)Prepare data batches.\nWrapping UpIn this article, we have discussed semantic segmentation using TensorFlow Keras.
"}}}},{"node":{"postTitle":"Neuromorphic Chip Market 2021 Precise Outlook –Intel Corporation, IBM Corporation, Eta Compute – KSU","slug":"neuromorphic-chip-market-2021-precise-outlook-intel-corporation-ibm-corporation-eta-compute-ksu","publishDate":"2021-05-15 00:00:00","createdLocal":"2021-05-15 14:30:50.531146","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"The Global Neuromorphic Chip Market Research Report 2021-2026, offers an in-depth evaluation of each crucial aspect of the Global Neuromorphic Chip industry that relates to market size, share, revenue, demand, sales volume, and development in the market.\nThe report analyzes the Neuromorphic Chip market over the values, historical pricing structure, and volume trends that make it easy to predict growth momentum and precisely estimate forthcoming opportunities in the Neuromorphic Chip Market.\nGet Sample PDF Copy of Latest Research on Neuromorphic Chip Market: (FLAT 25% OFF)https://www.marketinsightsreports.com/reports/01252567060/global-neuromorphic-chip-market-growth-status-and-outlook-2021-2026/inquiry?Mode=A19Global Major Players in Neuromorphic Chip Market are:Intel Corporation, IBM Corporation, Eta Compute, nepes, GrAI Matter Labs, GyrFalcon, aiCTX, BrainChip Holdings, and Other.\nInfluence of the Neuromorphic Chip Market report:–Comprehensive assessment of all opportunities and risks in the Neuromorphic Chip Market.\n–Favorable impression inside vital technological and market latest trends striking the Neuromorphic Chip Market.
"}}}},{"node":{"postTitle":"Image Recognition Market Global Analysis 2021-2028: Hitachi, Honeywell, Qualcomm, Google, Catchoom Technologies, and Many More. – Brockville Observer","slug":"image-recognition-market-global-analysis-2021-2028-hitachi-honeywell-qualcomm-google-catchoom-technologies-and-many-more-brockville-observer","publishDate":"None","createdLocal":"2021-05-15 14:30:49.914430","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"Introduction and ScopeThe global Image Recognition market research offers valuable insight into the current state of the local and global markets.\nVendor Landscape and Profiling:Major Companies CoveredHitachiHoneywellQualcommGoogleCatchoom TechnologiesAttrasoftLTU TechnologiesWikitudeSlyceNECWe Have Recent Updates of Image Recognition Market in Sample [email protected] https://www.orbisresearch.com/contacts/request-sample/5790161?utm_source=PoojaA5The Image Recognition market research often reveals highly lucrative markets that influence global market growth.\nGlobal Image Recognition industry research investigates all facets of the competitive environment and focuses on the worlds most influential businesses.\nThe Image Recognition report also delves into the industrys geographical landscape and the industries that control the global Image Recognition market.\nMarket Segmentation: Global Image Recognition MarketProduct-based Segmentation:Major Types CoveredCode RecognitionDigital Image ProcessingFacial RecognitionObject RecognitionPattern RecognitionOptical Character RecognitionApplication-based Segmentation:Major Applications CoveredBFSIMedia & EntertainmentRetail & Consumer GoodsIT & TelecomGovernmentHealthcareTransportation & LogisticsOthersBrowse Full Report with Facts and Figures of Image Recognition Market Report at @ https://www.orbisresearch.com/reports/index/image-recognition-market-global-analysis-2021-2028-insights-on-leading-players-type-applications-regions-and-future-opportunities?utm_source=PoojaA5The Image Recognition survey also covers major market share analysis, SWOT analysis, profitability index, and geographic distribution of the Image Recognition market.
"}}}},{"node":{"postTitle":"Artificial Intelligence in Transportation Market May Set a New Epic Growth Story","slug":"artificial-intelligence-in-transportation-market-may-set-a-new-epic-growth-story","publishDate":"None","createdLocal":"2021-05-15 14:30:49.252247","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"A Latest intelligence report published by AMA Research with title “Artificial Intelligence in Transportation Market Outlook to 2025.A detailed study accumulated to offer Latest insights about acute features of the Global Artificial Intelligence in Transportation market.\nThe automated vehicles requires machine intelligence that is artificial intelligence which refers to computer operated tasks which otherwise have required human intelligence such as decision making and visual perception.\nThe growing demand for Artificial Intelligence in Transportation markets will drive growth in the North American market over the next few years.\nChapter 3: Changing Impact on Market Dynamics- Drivers, Trends and Challenges & Opportunities of the Global Artificial Intelligence in Transportation; Post COVID AnalysisChapter 4: Presenting the Global Artificial Intelligence in Transportation Market Factor Analysis, Post COVID Impact Analysis, Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.\nWhat are different prospects and threats faced by the dealers in the Artificial Intelligence in Transportation market?
"}}}},{"node":{"postTitle":"Content Recognition Market Global Analysis 2021-2028: Enswers, Google, Nuance Communications, Viscovery, Beatgrid Media, and Many More. – Brockville Observer","slug":"content-recognition-market-global-analysis-2021-2028-enswers-google-nuance-communications-viscovery-beatgrid-media-and-many-more-brockville-observer","publishDate":"None","createdLocal":"2021-05-15 14:30:48.497100","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"The study encompasses profiles of major companies operating in the Content Recognition Market.\nThe report diversifies the global geographical expanse of Content Recognition market into five prominent regions such as Europe, APAC, MEA, North and South America.\nThe key regions covered in the Content Recognition market report are:North America (U.S., Canada, Mexico)South America (Cuba, Brazil, Argentina, and many others.)\n• Analyze the impact of government regulations on the profitability of the Content Recognition industryDo You Have Any Query or Specific Requirement?\nTable of ContentsChapter One: Report Overview1.1 Study Scope1.2 Key Market Segments1.3 Players Covered: Ranking by Content Recognition Revenue1.4 Market Analysis by Type1.4.1 Global Content Recognition Market Size Growth Rate by Type: 2020 VS 20281.5 Market by Application1.5.1 Global Content Recognition Market Share by Application: 2020 VS 20281.6 Study Objectives1.7 Years ConsideredChapter Two: Global Growth Trends by Regions2.1 Content Recognition Market Perspective (2015-2028)2.2 Content Recognition Growth Trends by Regions2.2.1 Content Recognition Market Size by Regions: 2015 VS 2020 VS 20282.2.2 Content Recognition Historic Market Share by Regions (2015-2020)2.2.3 Content Recognition Forecasted Market Size by Regions (2021-2028)2.3 Industry Trends and Growth Strategy2.3.1 Market Top Trends2.3.2 Market Drivers2.3.3 Market Challenges2.3.4 Porter’s Five Forces Analysis2.3.5 Content Recognition Market Growth Strategy2.3.6 Primary Interviews with Key Content Recognition Players (Opinion Leaders)Chapter Three: Competition Landscape by Key Players3.1 Global Top Content Recognition Players by Market Size3.1.1 Global Top Content Recognition Players by Revenue (2015-2020)3.1.2 Global Content Recognition Revenue Market Share by Players (2015-2020)3.1.3 Global Content Recognition Market Share by Company Type (Tier 1, Tier Chapter Two: and Tier 3)3.2 Global Content Recognition Market Concentration Ratio3.2.1 Global Content Recognition Market Concentration Ratio (CRChapter Five: and HHI)3.2.2 Global Top Chapter Ten: and Top 5 Companies by Content Recognition Revenue in 20203.3 Content Recognition Key Players Head office and Area Served3.4 Key Players Content Recognition Product Solution and Service3.5 Date of Enter into Content Recognition Market3.6 Mergers & Acquisitions, Expansion PlansAbout Us:Orbis Research (orbisresearch.com) is a single point aid for all your market research requirements.
"}}}},{"node":{"postTitle":"Enterprise Artificial Intelligence (AI) MarketProgresses for Huge Profits during 2026 – Test & Measurement","slug":"enterprise-artificial-intelligence-ai-marketprogresses-for-huge-profits-during-2026-test-measurement","publishDate":"None","createdLocal":"2021-05-15 14:30:47.131568","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"Moreover, escalating demand for analyzing and interpreting large amount of data boosts the requirement of artificial intelligence industry solutions.\nHowever, lack of trained and experienced staff hinders the growth of the enterprise Artificial Intelligence (AI) market.\nAlso, on-going developments in smart virtual assistants and robots are anticipated to be opportunistic for the growth of the enterprise artificial intelligence (AI) market.\nKEY BENEFITS• The report provides an in-depth analysis of the global enterprise artificial intelligence (AI) market trends, key driving factors, and potential areas for product investments.\n• The quantitative analysis of the global enterprise artificial intelligence (AI) market share from 2018 to 2026 is provided to determine the market potential.
"}}}},{"node":{"postTitle":"Google Arts & Culture Uses AI To Preserve Endangered Languages","slug":"google-arts-culture-uses-ai-to-preserve-endangered-languages","publishDate":"2021-05-15 10:30:00+00:00","createdLocal":"2021-05-15 14:30:46.194134","feedName":"Image Recognition","postSummary":{"childMarkdownRemark":{"html":"Google Arts & Culture has decided to apply Google’s technology to preserve endangered languages.\nWoolaroo is an interactive and educational tool to help promote endangered languages.\nGoogle wants to preserve and bring the world’s endangered languages online and accessible to anyone, anywhere.\nWhile developing the Woolaroo platform, Google collaborated with linguistic experts of these ten languages.\nThe programme can preserve endangered languages by creating a database online and educating people about them.
"}}}}]}},"pageContext":{"limit":8,"skip":2336,"irNumPages":301,"currentPage":293}}}