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Welcome to paddedetection. In view of the problems encountered in the process of using paddedetection, we have sorted the high-frequency situations into FAQs (frequently asked questions) Portal: https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.1/docs/tutorials/FAQ.md Github address is: https://github.com/PaddlePaddle/PaddleDetec ...

This paper mainly refers to DataWhale graph neural network team learning The statistics of the three data sets are as follows: data setCoraCiteSeerPubMedNumber of nodes2708332719717Number of sides5278455244324Number of training nodes14012060Number of verification nodes500500500Number of test nodes100010001000Number of node categories763Featur ...

neuron    the most basic concept in deep learning: neuron, the popular neural network, is almost composed of neurons combined in different ways. A complete neuron is mainly composed of two parts, namely linear function and excitation function.    linear function:      y = wX + b       the formulas o ...

1. General 1.1 introduction of convolutional neural network In the previous blog, we made an implementation of fully connected neural network. Among them, the input layer has 784 (28 * 28 picture) elements, the four hidden layers have 400, 300, 200 and 100 neurons respectively, and the output layer includes 10 categories of handwritten digits ...

be based on Estimation of battery SOH based on LSTM neural network    unlike BP neural network, RNN network not only considers the input of the previous time, but also gives the network the ability to remember the information of the previous time. Although RNN network has high accuracy, it has the problem of gradient disappe ...

In fact, most of the progress in image classification can be attributed to the improvement of training process, such as the increase of data and the change of optimization methods. However, most improvements are not described in detail. Therefore, the authors test and implement these improved methods in this paper, and evaluate the impact of th ...

Abstract: the content of this article is my understanding in the process of learning Deep Learning, and the code is written by myself (the code ability is not very strong). If there is something wrong, you are welcome to point out and correct it. Why use convolutional neural network There are two problems when processing pictures using a ...

6.1 parameter update SGDMomentumAdaGradAdam 6.1.1 SGD Simple but possibly inefficient, e.g. f = 0.05x2+y2Gradient direction: may not point to the lowest pointLocal minimum and global minimum` import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np def f(x,y): return np.power(x,2)/20 + np.power(y, ...

Detailed explanation of BN core parameters of PyTorchOriginal document: https://www.yuque.com/lart/ug...BN is a common operation and module in CNN. In the specific implementation, it contains multiple parameters. This also leads to different effects under different parameter combinations.affineModify during initializationWhen fine is set to Tru ...

Neural network foundation and multi class classification 3.1 model representation 3.1.1 why do we need neural networks Both linear regression and logistic regression learned in the first two sections have a disadvantage: when there are too many features, the calculation load will be very large. For example, in identifying whether a pictu ...