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    <title><![CDATA[StreamingMeme — Streaming Learning Center coverage]]></title>
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      <title><![CDATA[SLC Bitrate Explorer 2.0 adds portfolio-wide BD-Rate and cost analysis]]></title>
      <link><![CDATA[https://streaminglearningcenter.com/articles/sbe-portfolio-measuring-bd-rate-and-break-even-across-a-full-library.html]]></link>
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      <pubDate>Thu, 16 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[Streaming Learning Center has launched SLC Bitrate Explorer 2.0, adding a Portfolio feature to aggregate BD-Rate and cost-benefit analysis across full video libraries. This update allows streaming engineers to compare performance metrics and distribution costs across multiple codecs and encoding configurations.]]></description>
      <content:encoded><![CDATA[Streaming Learning Center has launched SLC Bitrate Explorer 2.0, adding a Portfolio feature to aggregate BD-Rate and cost-benefit analysis across full video libraries. This update allows streaming engineers to compare performance metrics and distribution costs across multiple codecs and encoding configurations.]]></content:encoded>
      <dc:creator><![CDATA[Streaming Learning Center]]></dc:creator>
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      <title><![CDATA[Missing color metadata tanks VMAF scores, causing 40-point quality measurement errors]]></title>
      <link><![CDATA[https://streaminglearningcenter.com/articles/computing-vmaf-its-all-about-the-edge-cases.html]]></link>
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      <pubDate>Mon, 22 Jun 2026 00:00:00 GMT</pubDate>
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      <description><![CDATA[Streaming Learning Center analyzed how missing color space and color range metadata in video files causes automated scaling steps in VMAF analysis tools to fail, resulting in inaccurate quality scores. The issue affects tools like Bitrate Explorer and FFMetrics when encoding outputs omit header metadata flags. Declaring the color metadata explicitly during scaling resolves the discrepancy, preventing false-negative QC results.]]></description>
      <content:encoded><![CDATA[Streaming Learning Center analyzed how missing color space and color range metadata in video files causes automated scaling steps in VMAF analysis tools to fail, resulting in inaccurate quality scores. The issue affects tools like Bitrate Explorer and FFMetrics when encoding outputs omit header metadata flags. Declaring the color metadata explicitly during scaling resolves the discrepancy, preventing false-negative QC results.]]></content:encoded>
      <dc:creator><![CDATA[Streaming Learning Center]]></dc:creator>
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      <title><![CDATA[What Is Media over QUIC (MoQ) and Why It Matters for Real-Time Streaming - Streaming Learning Center]]></title>
      <link><![CDATA[https://streaminglearningcenter.com/articles/what-is-media-over-quic-moq-and-why-it-matters-for-real-time-streaming.html]]></link>
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      <pubDate>Tue, 26 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[VIDEO_DELIVERY_AND_CDN]]></category>
      <description><![CDATA[This article introduces Media over QUIC (MoQ), a new QUIC-based protocol aiming to bridge the gap between WebRTC's real-time, low-latency interactivity and HLS/DASH's large-scale, CDN-friendly delivery. MoQ is described as delivering sub-second latency while maintaining CDN-scale capabilities, addressing a fundamental tension in live streaming protocols.]]></description>
      <content:encoded><![CDATA[This article introduces Media over QUIC (MoQ), a new QUIC-based protocol aiming to bridge the gap between WebRTC's real-time, low-latency interactivity and HLS/DASH's large-scale, CDN-friendly delivery. MoQ is described as delivering sub-second latency while maintaining CDN-scale capabilities, addressing a fundamental tension in live streaming protocols.]]></content:encoded>
      <dc:creator><![CDATA[Streaming Learning Center]]></dc:creator>
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      <title><![CDATA[Three Paths to Compression for Machine Vision: VCM, FCM, and the V-Nova Wild Card - Streaming Learning Center]]></title>
      <link><![CDATA[https://streaminglearningcenter.com/articles/three-paths-to-compression-for-machine-vision-vcm-fcm-and-the-v-nova-wild-card.html]]></link>
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      <pubDate>Tue, 26 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The article discusses three emerging compression standards tailored for machine vision applications: MPEG's Video Coding for Machines (VCM) and Feature Coding for Machines (FCM). It also mentions V-Nova's Low Complexity Enhancement Video Coding (LCEVC) as a solution that integrates AI and human perception requirements for video compression. These new approaches address the limitations of traditional codecs like H.264 and HEVC, which were designed for human viewing rather than AI-driven workflows.]]></description>
      <content:encoded><![CDATA[The article discusses three emerging compression standards tailored for machine vision applications: MPEG's Video Coding for Machines (VCM) and Feature Coding for Machines (FCM). It also mentions V-Nova's Low Complexity Enhancement Video Coding (LCEVC) as a solution that integrates AI and human perception requirements for video compression. These new approaches address the limitations of traditional codecs like H.264 and HEVC, which were designed for human viewing rather than AI-driven workflows.]]></content:encoded>
      <dc:creator><![CDATA[Streaming Learning Center]]></dc:creator>
      <author><![CDATA[Streaming Learning Center]]></author>
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      <title><![CDATA[Comparing H.264, HEVC, VP9, and AV1 in SBE: From BD-Rate to Contextual ROI - Streaming Learning Center]]></title>
      <link><![CDATA[https://streaminglearningcenter.com/articles/comparing-h-264-hevc-vp9-and-av1-in-sbe-from-bd-rate-to-contextual-roi.html]]></link>
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      <pubDate>Tue, 19 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The article discusses the common tool stack used by video engineers for codec comparison, highlighting the limitations of current tools for analyzing codecs like H.264, HEVC, VP9, and AV1. It specifically mentions MediaInfo, Bitrate Viewer, and Moscow State University VQMT, noting their critical gaps in providing comprehensive data for RD curves and BD-Rate.]]></description>
      <content:encoded><![CDATA[The article discusses the common tool stack used by video engineers for codec comparison, highlighting the limitations of current tools for analyzing codecs like H.264, HEVC, VP9, and AV1. It specifically mentions MediaInfo, Bitrate Viewer, and Moscow State University VQMT, noting their critical gaps in providing comprehensive data for RD curves and BD-Rate.]]></content:encoded>
      <dc:creator><![CDATA[Streaming Learning Center]]></dc:creator>
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      <title><![CDATA[SLC Bitrate Explorer: Encode Verification for Professionals]]></title>
      <link><![CDATA[https://streaminglearningcenter.com/articles/slc-bitrate-explorer.html]]></link>
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      <pubDate>Thu, 02 Apr 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[Streaming Learning Center describes SLC Bitrate Explorer, a Windows and macOS tool aimed at encoding engineers and QA teams for verifying test encodes before production. The software supports analysis of H.264, HEVC, VP9, and AV1 files, providing codec/bitstream parameter inspection, bitrate and frame-structure visualization, and objective quality metrics (VMAF, PSNR, SSIM), along with BD-Rate and cost breakeven calculations. The article outlines trial and free-tier limitations, paid licensing, and download links for platform-specific builds.]]></description>
      <content:encoded><![CDATA[Streaming Learning Center describes SLC Bitrate Explorer, a Windows and macOS tool aimed at encoding engineers and QA teams for verifying test encodes before production. The software supports analysis of H.264, HEVC, VP9, and AV1 files, providing codec/bitstream parameter inspection, bitrate and frame-structure visualization, and objective quality metrics (VMAF, PSNR, SSIM), along with BD-Rate and cost breakeven calculations. The article outlines trial and free-tier limitations, paid licensing, and download links for platform-specific builds.]]></content:encoded>
      <dc:creator><![CDATA[Streaming Learning Center]]></dc:creator>
      <author><![CDATA[Streaming Learning Center]]></author>
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      <title><![CDATA[Deep Render and the Streaming Learning Center: A Sustained Visibility and Validation Campaign]]></title>
      <link><![CDATA[https://streaminglearningcenter.com/news/deep-render-and-the-streaming-learning-center-a-sustained-visibility-and-validation-campaign.html]]></link>
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      <pubDate>Thu, 11 Dec 2025 00:00:00 GMT</pubDate>
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      <description><![CDATA[Deep Render entered 2024 with a working AI-based codec demonstrated live in FFmpeg and VLC, signaling a major step forward in video compression technology. The company is now focusing on sustained visibility and validation among streaming professionals to drive industry adoption.]]></description>
      <content:encoded><![CDATA[Deep Render entered 2024 with a working AI-based codec demonstrated live in FFmpeg and VLC, signaling a major step forward in video compression technology. The company is now focusing on sustained visibility and validation among streaming professionals to drive industry adoption.]]></content:encoded>
      <dc:creator><![CDATA[Streaming Learning Center]]></dc:creator>
      <author><![CDATA[Streaming Learning Center]]></author>
      
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