[traffic sign recognition] traffic sign recognition in haze weather based on matlab GUI BP neural network (with panel) [including Matlab source code phase 1771]

1, Brief introduction of BP neural network traffic sign recognition Road traffic signs are used to prohibit, warn, instruct and restrict road users to use roads in an orderly manner to ensure travel safety If the road traffic signs can be recognized automatically, the occurrence of road traffic accidents will be greatly reduced However, due to ...

Added by the182guy on Thu, 10 Mar 2022 10:19:15 +0200

[GNN benchmark] Figure benchmark data set of machine learning

Figure ImageNet of neural network? Open source millions of OGB benchmark data sets such as Stanford University In the small data full of "MNIST", does graph neural network also need a big benchmark such as "ImageNet"? Recently, Professor Jure Leskovec of Stanford University announced the open source of Open Graph Benchmar ...

Added by scopley on Wed, 09 Mar 2022 09:47:27 +0200

Practical learning notes of Pytrch neural network_ 12 (example) predicting the survival of passengers on the Titanic

1 sample processing 1.1 load sample code --- Titanic forecast Py (Part 1) import numpy as np import torch import torch.nn as nn import torch.nn.functional as F from scipy import stats import pandas as pd import matplotlib.pyplot as plt import os os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE" def moving_average(a, w=10):#Define a function to calcu ...

Added by skiingguru1611 on Wed, 09 Mar 2022 09:35:34 +0200

Prevent overfitting

Get more training data (data enhancement) Data enhancement using geometric transformations Geometric transformations such as flip, crop, rotation and translation are some commonly used data enhancement techniques. GAN based data enhancement Reduce network capacity The simplest way to prevent overfitting is to reduce the size of the mod ...

Added by naveendk.55 on Tue, 08 Mar 2022 11:52:36 +0200

Reinforcement learning algorithm: PPO2 creates a bitcoin trading robot that won't lose money

Creating a bitcoin trading robot will not lose money In this article, we will create a deep reinforcement learning agent to learn to make money through bitcoin trading. In this tutorial, we will use the PPO agent in OpenAIgym and the stable baselines Library (a branch of OpenAI's baselines Library). The purpose of this series of articles is to ...

Added by decessus on Mon, 07 Mar 2022 21:53:14 +0200

Python machine learning example -- price prediction using neural network

This article mainly records the process of using machine learning to solve the problems I encounter. catalogue 1, Problem description 2, Data processing 2.1 treatment of missing values 2.2 abnormal value handling 2.3 characteristic Engineering 3, Dimensionality reduction 4, Model establishment 5, Model training 1, Problem description ...

Added by kulikedat on Sun, 06 Mar 2022 12:43:03 +0200

Detailed explanation of emotion analysis using two-way LSTM

1, Principle introduction RNN can remember context information, so it is often used to process time series data. In theory, RNN can memorize infinite length of historical information, but due to the accumulation of gradients, the amount of calculation is too large to be operated in practice. Therefore, in practice, RNN can only record the info ...

Added by Randomizer on Fri, 04 Mar 2022 16:53:07 +0200

Interpretability study - XGNN

Paper core target Here, the author aims at the graph classification problem of GNN. Study the model level interpretation method. The specific way is to train a graph generator use f ( . ) f(.) ...

Added by JoeyT2007 on Thu, 03 Mar 2022 21:14:30 +0200

Study notes on lightweight network structure mobilenetv1, v2 and v3

Today, I'm going to take a simple note of mobilenet. I'm afraid I'll forget the relevant contents of mobilenet. First of all, we need to know that mobilenet is a model framework that can be used on embedded devices. Therefore, its biggest advantage is that it has less parameters, and we still need to ensure that the accuracy of computer vision ...

Added by sunnyside on Sun, 27 Feb 2022 02:07:34 +0200

Two methods: building neural network eight strand six step method

The difference between the two methods: Sequential network building method. The upper output is the Sequential network structure of the lower input, but it is impossible to write some non Sequential network structures with hops. At this time, we can choose to use class to build a neural network structure, and class can be used to encapsulate a ...

Added by nepton on Wed, 23 Feb 2022 16:42:38 +0200