首页|Studies Conducted at Technical University of Denmark (DTU) on Artificial Intelli gence Recently Reported (Remote 3d Imaging and Classification of Pelagic Microor ganisms With a Short-range Multispectral Confocal Lidar)
Studies Conducted at Technical University of Denmark (DTU) on Artificial Intelli gence Recently Reported (Remote 3d Imaging and Classification of Pelagic Microor ganisms With a Short-range Multispectral Confocal Lidar)
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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."
RoskildeDenmarkEuropeArtificial In telligenceEmerging TechnologiesMachine LearningTechnical University of Den mark (DTU)
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