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Found 3 papers, 2 papers with code
Your time series is worth a binary image: machine vision assisted deep framework for time series forecasting
To address this challenge, this paper proposes a novel machine vision assisted deep time series analysis (MV-DTSA) framework.
Rubik's Cube Operator: A Plug And Play Permutation Module for Better Arranging High Dimensional Industrial Data in Deep Convolutional Processes
The convolutional neural network (CNN) has been widely applied to process the industrial data based tensor input, which integrates data records of distributed industrial systems from the spatial, temporal, and system dynamics aspects.
Generative Wind Power Curve Modeling Via Machine Vision: A Self-learning Deep Convolutional Network Based Method
First, different from traditional studies regarding the WPC modeling as a curve fitting problem, in this paper, we renovate the WPC modeling formulation from a machine vision aspect.
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