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预测太平洋 (Crassostrea gigas) 新鲜度的智能方法使用深度学习与马隆迪甲基和总硫基组信息融合

Tao Lu1,2, Fanqianhui Yu3,4,5, Baokun Han6

  • 1School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China.

Foods (Basel, Switzerland)
|October 14, 2023
PubMed
概括

本研究介绍了一种人工智能方法,用于快速,非破坏性的的新鲜度检测,使用深度学习和化学标记. 该系统准确地预测了malondialdehyde (MDA) 和总硫 (SH) 含量,从而能够精确地评估新鲜度.

关键词:
卷积神经网络是一种卷积神经网络.功能可视化 功能可视化新鲜度预测 预测 新鲜度一个的.最强大的激活.

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The deep ocean and its underlying sediments represent vast, largely unexplored microbial habitats that extend far beyond the sunlit photic zone. The photic (euphotic) zone typically spans the upper ~100–200 meters of pelagic waters in the open ocean, but its depth varies geographically and seasonally, where sufficient light supports photosynthetic life. Below this lies the deep sea, spanning roughly 1000–6000 meters (bathypelagic to abyssal zones), with deeper hadal trenches...
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