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Found 4 papers, 0 papers with code
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws
In this work, we introduce conservation law-encoded neural operators (clawNOs), a suite of NOs that endow inference with automatic satisfaction of such conservation laws.
Zero-sample surface defect detection and classification based on semantic feedback neural network
Defect detection and classification technology has changed from traditional artificial visual inspection to current intelligent automated inspection, but most of the current defect detection methods are training related detection models based on a data-driven approach, taking into account the difficulty of collecting some sample data in the industrial field.
A self-adapting super-resolution structures framework for automatic design of GAN
In this paper, we introduce a new super-resolution image reconstruction generative adversarial network framework, and a Bayesian optimization method used to optimizing the hyperparameters of the generator and discriminator.
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN
The generator consists of feature extraction and image reconstruction.
