摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx编辑在Roskilde，Denma Rk的新闻报道，研究表明：“浮游生物对维持健康的水生生态系统至关重要，因为它影响着全球的生物碳泵。然而，气候变化引起的海洋性质的改变威胁着浮游生物群落。”我们的新闻记者从丹麦技术大学(DTU)的研究中获得了一句话：“因此，监测它们的丰度对于评估海洋生态系统的健康状况至关重要。原位光学工具解锁了亚毫米样品的高分辨率测量，但最新成像技术仅限于固定的和小的近距离体积，从而使仪器能够垂直俯冲。这里，本文介绍了一种新型的扫描多波共焦光检测测距系统(LiDAR),该系统将非弹性控制原理扩展到多波长通道。利用近衍射极限形态学和光谱学相结合的方法获取4D PO INT云，用于人工智能(AI)模型的训练。演示了微塑料的体积制图和分类，可以根据颜色和形状对它们进行分类。此外，还从自由游动的浮游动物和微藻群落中分辨出体内的自体荧光。该光子平台沿人工智能模型的部署克服了人工识别浮游生物的复杂和主观的任务，实现了从固定的有利位置进行非侵入性传感，介绍了一种新型的水下自荧光近程传感多光子发射共焦光检测成像系统(LiDAR),该系统将三维高分辨率形态数据与体素级光谱信息结合起来。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting out of Roskilde, Denma rk, by NewsRx editors, research stated, "Plankton is essential to maintain healt hy aquatic ecosystems since it influences the biological carbon pump globally. H owever, climate change-induced alterations to oceanic properties threaten plankt onic communities." Our news journalists obtained a quote from the research from the Technical Unive rsity of Denmark (DTU), "It is therefore crucial to monitor their abundance to a ssess the health status of marine ecosystems. In situ optical tools unlock high- resolution measurements of sub-millimeter specimens, but state-of-theart underw ater imaging techniques are limited to fixed and small close-range volumes, requ iring the instruments to be vertically dived. Here, a novel scanning multispectr al confocal light detection and ranging (LiDAR) system for short-range volumetri c sensing in aquatic media is introduced. The system expands the inelastic confo cal principle to multiple wavelength channels, allowing the acquisition of 4D po int clouds combining near-diffraction limited morphological and spectroscopic da ta that is used to train artificial intelligence (AI) models. Volumetric mapping and classification of microplastics is demonstrated to sort them by color and s ize. Furthermore, in vivo autofluorescence is resolved from a community of free- swimming zooplankton and microalgae, and accurate spectral identification of dif ferent genera is accomplished. The deployment of this photonic platform alongsid e AI models overcomes the complex and subjective task of manual plankton identif ication and enables non-intrusive sensing from fixed vantage points, thus consti tuting a unique tool for underwater environmental monitoring. A novel multispect ral confocal light detection and imaging (LiDAR) system for underwater autofluor escence short-range sensing is introduced. The instrument combines 3D high-resol ution morphological data with spectroscopic information at the voxel level."
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