Scientific Research Publishing

Yao, S., Zhao, W., Wu, C. and Chen, W. (2023) Nonlinear Constitutive Calculation Method of Rarefied Flow Based on Deep Convolution Neural Networks. Physics of Fluids, 35 ...

ABSTRACT: The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant ...
GitHub

Inception in TensorFlow

ImageNet is a common academic data set in machine learning for training an image recognition system. Code in this directory demonstrates how to use TensorFlow to train and evaluate a type of ...
GitHub

The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple ...

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Hosted on MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...
IEEE

A Tutorial on Quantum Convolutional Neural Networks (QCNN)

Abstract: Convolutional Neural Network (CNN) is a popular model in computer vision and has the advantage of making good use of the correlation information of data. However, CNN is challenging to learn ...
pv magazine International

Ultra-short-term PV forecasting based on convolutional neural network, long short-term memory

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...