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Found 5 papers, 1 papers with code
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.
Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN
The generator consists of feature extraction and image reconstruction.
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.
Anharmonic Raman spectra simulation of crystals from deep neural networks
Raman spectroscopy is an effective tool to analyze the structures of various materials as it provides chemical and compositional information.
DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models
Materials 3, 023804] and is capable of generating uniformly accurate deep learning based PES models in a way that minimizes human intervention and the computational cost for data generation and model training.
Computational Physics
