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Creators/Authors contains: "Cho, Minsik"

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  1. ; ; ; ; ; (, Journal of Chemical Theory and Computation)
    Free, publicly-accessible full text available December 24, 2025
  2. ; ; ; ; (, HotMobile '20: Proceedings of the 21st International Workshop on Mobile Computing Systems and Applications)
    null (Ed.)
    We propose DeepFind, an on-device acceleration engine for mobile-native spatial exploratory applications that utilize deep-learning architectures such as CNNs. DeepFind leverages the fact that input frames exhibit high visual dynamicity, of which a dominant portion actually comes from the camera’s own motion. We develop lightweight sensor-based transformations and perspective-normalized global buffer management to replace expensive convolution operations, effectively speeding up CNN inference. DeepFind achieves a win-win – lightweight reusability determination coupled with avoiding a large amount of convolution operations, creating a virtuous cycle: smaller inter-frame differential leads to faster per-frame computation, yielding even smaller inter-frame differential and so on. 
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    Accepted Manuscript Full Text Available
  3. ; ; (, Journal of Chemical Theory and Computation)
    Full Text Available 
  4. ; ; ; ; ; ; ; ; ; ; et al (, Nature Reviews Physics)
    Full Text Available