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您的检索式：作者名="Longbin Zeng"
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| 1 | DTBVis:An interactive visual comparison system for digital twin brain and human brain显示文摘The digital twin brain(DTB)computing model from brain-inspired computing research is an emerging artificial intelligence technique,which is realized by a computational modeling approach of hardware and software.It can achieve various cognitive abilities and their synergistic mechanisms in a manner similar to the human brain.Given that the task of the DTB is to simulate the functions of the human brain,comparing the similarities and differences between the two is crucial.However,the visualization study of the DTB is still under-researched.Moreover,the complexity of the datasets(multilevel spatiotemporal granularity and different types of comparison tasks)presents new challenges to the analysis and exploration of visualization.Therefore,in this study,we proposed DTBVis,a visual analytics system that supports comparison tasks for the DTB.DTBVis supports iterative explorations from different levels and at different granularities.Combined with automatic similarity recommendation,and high-dimensional exploration,DTBVis can assist experts in understanding the similarities and differences between the DTB and the human brain,thus helping them adjust their model and enhance its functionality.The highest level of DTBVis shows an overview of the datasets from the brain,which is used for comparison and exploration of the function and structure of the DTB and the human brain.The medium level is used for the comparison and exploration of a designated brain region.The low level can analyze a designated brain voxel.We worked closely with experts of brain science and held regular seminars with them.Feedback from the experts indicates that our approach helps them conduct comparative studies of the DTB and human brain and make modeling adjustments of the DTB through intuitive visual comparisons and interactive explorations. | Yuxiao Li Xinhong Li Siqi Shen Longbin Zeng Richen Liu Qibao Zheng Jianfeng Feng | 2023 | Visual Informatics2023，7，2： | 1 |
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