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RapidFlow - GitHub To address these two problems, we propose RapidFlow, an effective approach to CSM First, we design a query reduction technique, which reduces CSM to batch subgraph matching (BSM) where we enumerate all results in a region of 𝐺 that will be affected by the update
RAPIDFlow: Recurrent Adaptable Pyramids with Iterative Decoding for . . . fully recurrent encoder-decoder structure to estimate optical flow with reduced computational costs Our RAPIDFlow model has a recurrent encoder that can be dynamically chan ed during inference to produce feature pyramids of various lengths to better adapt to the input size The experiments on an embedded system show that our model can
RapidFlow: an efficient approach to continuous subgraph matching . . . To address these two problems, we propose RapidFlow, an effective approach to CSM First, we design a query reduction technique, which reduces CSM to batch subgraph matching (BSM) where we enumerate all results in a region of G that will be affected by the update
RapidFlow | ThermoAnalytics RapidFlow™ is a 3D flow solver integrated with TAITherm™ and MuSES™, designed for airflow applications and convection heat transfer analysis It offers fast, high-fidelity results, works on complex geometries, and is easy to use with minimal setup time
RAPIDFlow: Recurrent Adaptable Pyramids with Iterative Decoding for . . . Extracting motion information from videos with optical flow estimation is vital in multiple practical robot applications Current optical flow approaches show remarkable accuracy, but top-performing methods have high computational costs and are unsuitable for embedded devices Although some previous works have focused on developing low-cost optical flow strategies, their estimation quality has