GET https://dev.normadoc.fr/products-list/main/ics-2277/33-telecommunications-audio-and-video-engineering-4436/33-160-audio-video-and-audiovisual-engineering-4448/3…

Response
200 OK
IP
216.73.216.19
Profiled on
Token
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Components

5 Twig Components
5 Render Count
17 ms Render Time
74.0 MiB Memory Usage

Components

Name Metadata Render Count Render Time
PageBanner 
"App\Twig\Components\PageBanner"
components/PageBanner.html.twig 		1 4.92ms
BackButton 
"App\Twig\Components\BackButton"
components/BackButton.html.twig 		1 0.25ms
ProductCard 
"App\Twig\Components\ProductCard"
components/ProductCard.html.twig 		1 11.65ms
ProductState 
"App\Twig\Components\ProductState"
components/ProductState.html.twig 		1 0.22ms
ProductMostRecent 
"App\Twig\Components\ProductMostRecent"
components/ProductMostRecent.html.twig 		1 0.76ms

Render calls

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Input props 
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Component 
App\Twig\Components\PageBanner {#94179
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Component 
App\Twig\Components\BackButton {#94281
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Input props 
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App\Twig\Components\ProductState {#94936
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        #name: "IEEE 3333.1.3:2022"
        #slug: "ieee-3333-1-3-2022-ieee00007136-243785"
        #description: """
          New IEEE Standard - Active.<br />\n
          Measuring quality of experience (QoE) aims to explore the factors that contribute to a user’s perceptual experience including human, system, and context factors. Since QoE stems from human interaction with various devices, the estimation should be started by investigating the mechanism of human visual perception. Therefore, measuring QoE is still a challenging task. In this standard, QoE assessment is categorized into two subcategories which are perceptual quality and virtual reality (VR) cybersickness. In addition, deep learning models considering human factors for various QoE assessments are covered, along with a reliable subjective test methodology and a database construction procedure.<br />\n
          \t\t\t\t<br />\n
          This standard defines deep learning-based metrics of content analysis and quality of experience (QoE) assessment for visual contents, which is an extension of the standard for the QoE and visual-comfort assessments of three-dimensional (3D) contents based on psychophysical studies (IEEE Std 3333.1.1) and the standard for the perceptual quality assessment of 3D and ultra-high definition (UHD) contents (IEEE Std 3333.1.2). The scope covers the following. * Deep learning models for QoE assessment (multilayer perceptrons, convolutional neural networks, deep generative models) * Deep metrics of visual experience from High Definition (HD), UHD, 3D, High Dynamic Range (HDR), Virtual Reality (VR) and Mixed Reality (MR) contents * Deep analysis of clinical (electroencephalogram (EEG), electrocardiogram (ECG), electrooculography (EOG), and so on) and psychophysical (subjective test and simulator sickness questionnaire (SSQ)) data for QoE assessment * Deep personalized preference assessment of visual contents * Building image and video databases for performance benchmarking purpose if necessary
          """
        #metaKeywords: null
        #metaDescription: null
        #shortDescription: "IEEE Standard for the Deep Learning-Based Assessment of Visual Experience Based on Human Factors"
        -notes: "Active"
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