Recurrent flow refinement
WebMar 21, 2024 · The short-term bus passenger flow prediction of each bus line in a transit network is the basis of real-time cross-line bus dispatching, which ensures the efficient utilization of bus vehicle resources. As bus passengers transfer between different lines, to increase the accuracy of prediction, we integrate graph features into the recurrent neural … WebBrowse Encyclopedia. (1) The process of heating and melting the solder that has been screen printed onto a printed circuit board in order to bond chips and other components …
Recurrent flow refinement
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WebNov 1, 2024 · We introduce Recurrent All-Pairs Field Transforms (RAFT), a new deep network architecture for optical flow. RAFT extracts per-pixel features, builds multi-scale 4D correlation volumes for all... WebNov 1, 2024 · Categories: Soldering Articles. Author: Neoden USA. The infrared reflow soldering process is a common method for the rapid mass production of printed circuit …
WebJun 18, 2024 · Techopedia Explains Gated Recurrent Unit As a refinement of the general recurrent neural network structure, gated recurrent units have what's called an update … WebAn Unified Recurrent Video Object Segmentation Framework for Various Surveillance Environments ... the motion refinement block with multi-scale dense residual is proposed to combine the features from the optical flow encoder stream and the last REAM module for holistic feature learning. Finally, these holistic features and REAM features are ...
WebJan 1, 2024 · The flow refinement module of EFENet exploits globally the temporal information for flow enhancement, and therefore reduces alignment errors. Extensive experiments demonstrate the superior performance of our method in comparison to the state-of-the-art methods. 2 Related Work 2.1 Single-Image Super-Resolution WebData assimilation in subsurface flow systems is challenging due to the large number of flow simulations often required, and by the need to preserve geological realism in the calibrated (posterior) models. ... a 3D recurrent residual U-Net (referred to as recurrent R-U-Net), consists of 3D convolutional and recurrent (convLSTM) neural networks ...
WebMar 15, 2024 · The combination of the proposed RecSPy network and the proposed energy-based refinement enables our system to estimate optical flow effectively and efficiently. Experimental results on the benchmarks validate the effectiveness and efficiency of the proposed method.
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