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8abf63c8006d1d3f7ee9 · Unraveling Low Abundance Intimate Mixtures with Deep Learning

Unraveling Low Abundance Intimate Mixtures with Deep Learning

The high-confidence detection and identification of very low abundance, subpixel quantities of solid materials in nonlinear/intimate mixtures are still significant challenges for hyperspectral imagery (HSI) data analysis. We compare the ability of a

Официальный источник · 2019-05-14

Полные импортированные сведения карточки
{
  "title_en": "Unraveling Low Abundance Intimate Mixtures with Deep Learning",
  "designation": "",
  "series": "",
  "status": "",
  "date": "2019-05-14",
  "date_original": "May 14, 2019",
  "url": "https://www.nist.gov/publications/unraveling-low-abundance-intimate-mixtures-deep-learning",
  "source": "NIST Publications",
  "display_en": "",
  "authors_en": "Ronald G. Resmini, Kevin Christiansen, David Allen",
  "abstract_excerpt_en": "The high-confidence detection and identification of very low abundance, subpixel quantities of solid materials in nonlinear/intimate mixtures are still significant challenges for hyperspectral imagery (HSI) data analysis. We compare the ability of a",
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  "sources": [
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    {
      "title_en": "Unraveling Low Abundance Intimate Mixtures with Deep Learning",
      "designation": "",
      "series": "",
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      "date": "2019-05-14",
      "date_original": "May 14, 2019",
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      "source": "NIST Publications",
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      "authors_en": "Ronald G. Resmini, Kevin Christiansen, David Allen",
      "abstract_excerpt_en": "The high-confidence detection and identification of very low abundance, subpixel quantities of solid materials in nonlinear/intimate mixtures are still significant challenges for hyperspectral imagery (HSI) data analysis. We compare the ability of a"
    }
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