Detailed explanation of Shifted Window algorithm
Swin Transformer
Author: elfin Source: Swin
Original link: https://www.cnblogs.com/dan-baishucaizi/p/14661164.html
catalogue
abstract1. Introduction2. Related work
2.1 CNN and its variants2.2 self attention mechanism based on backbone structure2.3 self attention / transformers as a supplement to CNNs2.4 Transformer based b ...
Posted by Frozenlight777 on Tue, 18 Jan 2022 04:30:50 +0100
The gospel of the Bonaparte, using Python to "gather the wool and get all the music and movies you want"
1, Necessary environment
Recommend a URL analysis website, this website( http://music.zhuolin.wang/ )It's a little awesome. You can analyze VIP videos and VIP music.
If you don't download a large number of music, you can search and download directly here, modify the file name after downloading, and click playlist - click sync on this website ...
Posted by ILYAS415 on Tue, 18 Jan 2022 04:19:05 +0100
Pytoch actual combat_ Compression of neural networks
1. Compression of neural network
For some large-scale neural networks, their network structure is very complex (it is said that some neural networks of Huawei are composed of hundreds of millions of neurons). It is difficult for us to put this neural network on a small device (such as our apple watch). This requires us to be able to compress t ...
Posted by ttroy on Tue, 18 Jan 2022 01:29:10 +0100
11. Integrated learning practice
API parsing
AdaBoost algorithm (reduction coefficient needs to be added to solve the problem of infinite amplification caused by abnormal data, resulting in error)
parameter AdaBoostClassifier AdaBoostRegressor
base_estimator
Weak classifier object, the default is CART classification tree DecisionTreeClassifier;
Weak regressor object, the ...
Posted by DocUK on Mon, 17 Jan 2022 23:56:47 +0100
Python implements link prediction of protein interactions based on graph neural network
Guide
IntroModelDatasetInstallCiteReference
Intro
At present, it mainly realizes link prediction based on protein data under [data/yeast/yeast.edgelist].
Model
Model
The model mainly uses graph neural network, such as gae, vgae, etc
1.GCNModelVAE(src/vgae): volume product self coding and variational volume product self coding (self codi ...
Posted by Avochelm on Mon, 17 Jan 2022 14:55:54 +0100
Distributed operation Barrier of PyTorch
Distributed operation Barrier of PyTorchOriginal document: https://www.yuque.com/lart/ug...On the concept of barrierFor the concept of barrier, please refer to the introduction in Wiki: synchronization barrier is a synchronization method in parallel computing. For a group of processes or threads, a synchronization barrier in the program means t ...
Posted by red-x on Mon, 17 Jan 2022 12:53:18 +0100
Web crawler + deep learning LSTM model prediction lottery happy 8 lottery course
Web crawler + deep learning to predict happiness 8 lottery winning tutorial
background
Happy 8 lottery inquiry: https://www.zhcw.com/kjxx/kl8/ Happy 8 game rules: https://www.zhcw.com/c/2020-09-22/618869.shtml Theme of this project: use crawler to crawl the winning information of lottery happy 8 and use LSTM to predict.
import json
import m ...
Posted by okok on Mon, 17 Jan 2022 07:17:16 +0100
Tensorflow2.0 data and deployment - tensorflow advanced model deployment
1, TF Serving
Tensorflow Serving is a part of TFX (Tensorflow Extended). It is an API dedicated to machine learning services in the production environment. Using TF Serving, different versions of models can be accessed through HTTP on the cloud platform.
The following figure shows the process that needs to be experienced in the actual pro ...
Posted by Nathaniel on Mon, 17 Jan 2022 02:07:02 +0100
Five implementation strategies of pytoch's spatial shift operation
Five implementation strategies of pytoch's spatial shift operationThis article has authorized the platform of the polar city and is the official account of the polar platform. No second reprint is allowed without permissionOriginal document (may be further updated): https://www.yuque.com/lart/ug...prefacePreviously, I read some papers that use ...
Posted by daveoffy on Sun, 16 Jan 2022 21:33:02 +0100
TensorFlow realizes Denoising Autoencoder
Denoising autoencoder (DAE)
Before introducing the denoising autoencoder (DAE), first introduce an example of the use scene of DAE. When we take photos at night or in other dark environments, our photos are always filled with a lot of noise, which seriously affects the image quality, and the purpose of DAE is to remove the noise in these i ...
Posted by kcpaige89 on Sun, 16 Jan 2022 04:13:03 +0100