Researchers from the Aerospace Information Research Institute of the Chinese Academy of Sciences leveraged the advanced capabilities of SDGSAT-1's Glimmer Imager and Thermal Infrared Spectrometer to monitor gas flaring activities in the South China Sea.
A research team from the Xinjiang Institute of Physics and Chemistry of CAS proposed a graph machine learning model, namely TREE, based on the Transformer framework. With this novel Transformer-based architecture, TREE not only identifies the most influential omics data type but also detects the most representative network paths involved in regulating genes that drive cancer formation and progression.
A research team led by Prof. DONG Erbao from the University of Science and Technology of China of the Chinese Academy of Sciences, collaborating with Prof. YU Xinge from the City University of Hong Kong, developed a novel tactile perception method based on the structural color of flexible grating structural color.
In many Asian regions, especially in China, agricultural fields are typically small, scattered, and lack of clear boundaries, which complicates effective crop distribution and agricultural analysis using remote sensing technology. Now, a research group from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, addressed this challenge with a novel dual-branch deep learning model (DBL) they developed.
A research team led by Prof. ZHANG Ze from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences developed a Hyper-sampling Imaging (HSI) technology that enhances the image quality and resolution of digital imaging system.
A research team led by LI Xuefei at the Shenzhen Institutes of Advanced Technology, collaborating with TIAN Liang’s team from the Hong Kong Baptist University, developed a deconvolution algorithm called DeSide. This algorithm, based on deep learning and publicly available scRNA-seq datasets, can accurately estimate the abundance of 16 cell types across 19 types of solid tumors.
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