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Multisensor fusion localization Chapter 8 advanced fusion method based on filtering Reference blog: Deep Blue College - multi-sensor fusion positioning - Chapter 7 operation Code download: https://github.com/kahowang/sensor-fusion-for-localization-and-mapping/tree/main/%E7%AC%AC%E4%BA%94%E7%AB%A0%20%E6%83%AF%E6%80%A7%E5%AF%BC%E8%88%AA%E5%8E%9 ...

Catalogue of series articles PyTorch Week 3 - nn.MaxPool2d, nn.AvgPool2d, nn.Linear, active layer PyTorch Week 3 - convolution PyTorch Week 3 -- container of nn.Module: Sequential, ModuleList, ModuleDice PyTorch Week 3 - model creation PyTorch Week 2 - Dataloader and Dataset PyTorch Week 1 preface In this section, the principle of gradie ...

Official website project introduction Source framework Download 1. Practice introduction In this project, we will implement the inference algorithm of Bayesian network, especially variable elimination and perfect information value calculation. These reasoning algorithms will be able to infer the existence of invisible particles and ghosts. A ...

abstract SMOTE is a synthetic data algorithm for comprehensive sampling, which is used to solve the unbalanced class problem and synthesize data by combining a few over sampling classes and most under sampling classes. This article will take Nitesh V. Chawla(2002) This paper expounds the core idea of SMOTE and its naive algorithm, compares the ...

        The traditional statistical language model is a nonparametric model, that is, the conditional probability is estimated directly by counting, but the main disadvantage of this nonparametric model is poor generalization and can not make full use of similar context          The ...

Brief introduction This code is divided into three parts: Face input module: input it before recognition. Input it hereFace recognition module: after entering, the recognition is finishedCommon function module: take down the common modules in modules 1 and 2 and put them together Anecdotes outside the code (anecdote) I typed the code li ...

1. Introduction of GloVe word vector GloVe: The full name is Global Vectors for Word Representations. Its document [2] was presented at the EMNLP conference in 2014. It combines the idea of word vector and matrix decomposition to pre-train the original corpus and get a low-dimensional, continuous and sparse representation. Visualizing the pre- ...

1. Introduction to algorithm         The working principle of k-nearest neighbor algorithm is that there is a sample data set, also known as training sample set, and each data in the sample set has a label, that is, we know the corresponding relationship between each data in the sample set and its classificat ...

1, Introduction to immune algorithm 1 Introduction The word "Immune" is derived from Latin. Long ago, it was noted that patients with infectious diseases will have varying degrees of immunity to the disease after recovery. In medicine, immunity refers to a physiological response of the body to contact antigenic foreign bodies. In 195 ...

1. Introduction to data enhancement When there are few pictures in our training set, it is easy to cause over fitting of the network. In order to avoid this situation, we generally need to increase some picture data artificially through image processing, which will increase the number of available pictures and reduce the possibility of over ...