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Buyers' Guide 购买指南
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202470414
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引用次数: 0
Company Index 公司索引
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202470415
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引用次数: 0
Laser cleaning of insect residue without surface alteration 激光清除昆虫残留物，不改变表面结构
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202400025
Lewin Rathmann, Tim Radel

Insect residues disturb and interrupt the laminar air flow on airplane wings after a while. These residues therefor e need to be repeatedly removed. Shock wave-based laser cleaning of insect residue on stainless steel (1.4544.9) is presented as a possible method to reduce insect residues in a single pass and without influencing the base material, as confocal laser-scanning microscope images demonstrate.

昆虫残留物会在一段时间后干扰和中断飞机机翼上的层流气流。因此，需要反复清除这些残留物。激光共聚焦扫描显微镜图像显示，基于冲击波的激光清洁不锈钢（1.4544.9）上的昆虫残留物是一种可行的方法，可一次性减少昆虫残留物，且不会影响基体材料。
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引用次数: 0
Laser cleaning of insect residue without surface alteration 激光清除昆虫残留物，不改变表面结构
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202470409
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引用次数: 0
Optimized powder bed laser melting processes 优化粉末床激光熔融工艺
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202470410
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引用次数: 0
3D vision helps to precisely palletize parts 3D 视觉帮助精确码垛零件
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202470407
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引用次数: 0
Products: PhotonicsViews 4/2024 产品：PhotonicsViews 4/2024
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202470403
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引用次数: 0
Organizations & Initiatives: PhotonicsViews 4/2024 组织与倡议：PhotonicsViews 4/2024
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202470405
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引用次数: 0
Pioneering the future of integrated photonics 开创集成光子学的未来
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202470401
Jorn Smeets
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引用次数: 0
The importance of image quality in AI visual inspection systems 图像质量在人工智能视觉检测系统中的重要性
PhotonicsViews
Pub Date : 2024-09-01 DOI: 10.1002/phvs.202400027
Sagi Dolberg

The use of AI for visual inspection is currently making great strides in sectors like automotive, metals and machinery manufacturing. However, those investing in the technology not only expect a system that will be superior to manual inspection, but an error rate close to zero in defect detection. Let us look at the importance of image quality and why the variability in the production environment is the single greatest challenge that AI engineers must face.

目前，人工智能在视觉检测领域的应用正在汽车、金属和机械制造等行业取得长足进步。然而，投资这项技术的人不仅期望系统优于人工检测，还期望缺陷检测的错误率接近于零。让我们来看看图像质量的重要性，以及为什么生产环境的多变性是人工智能工程师必须面对的最大挑战。
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引用次数: 0
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