A recent study titled Programmable Multidimensional Diffraction Engineering via an Optically Addressed Nested Fourier Metasurface has been published in Nanophotonics. The work was led by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Sciences, with collaborators from the State Key Laboratory of Hybrid Rice at the Hunan Academy of Agricultural Sciences, Qualcomm Inc., and Soleilware Photonics LLC.
A recent study titled "Variable-length multiobjective optimization of inspection schedules for condition-based maintenance of vertical-cavity surface-emitting lasers under imperfect detection" has been published in Reliability Engineering and System Safety. The study was conducted by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Sciences. The framework jointly selects inspection count and timing and the degradation thresholds for servicing or replacement.
The researchers combined aqueous gel casting and silicon infiltration to form dense diamond-silicon carbide composites from highly loaded slurries. The diamond-rich composition increased flexural strength by 84.5 percent over the diamond-free reference and also delivered a higher elastic modulus. It further reduced residual silicon while maintaining near-full densification, linking the mechanical improvement to the formation of a more continuous ceramic network.
A recent study titled “Dual-input remote sensing image fusion for object detection based on hybrid-level Mamba fusion” has been published in Pattern Recognition. The work was conducted by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Sciences. The team developed a hybrid-level dual-input Mamba framework that links feature fusion with final decisions.
A recent study titled "EGHF-Net: Geometry-guided deformable cross-attention for event-RGB semantic segmentation with spatio-temporal alignment" has been published in Expert Systems with Applications. Conducted jointly by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Sciences and the University of Toronto, the work introduced EGHF-Net to align event-camera signals with conventional RGB images for semantic segmentation.
In a study published in Smart Agricultural Technology, a research group led by ZHAO Qinglei from the Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP) of the Chinese Academy of Sciences, together with collaborators, developed a deep learning method for screening high-vigor maize seeds before germination using ordinary RGB images.
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