## Kalman filter for tracking and prediction of moving targets on images

Kalman filter for tracking and prediction of moving targets on images
brief introduction
Kalman filter predicts the current state through the previous state and uses the current observation state for correction The direct measurements are left, top, right and bottom, representing the upper left and lower right coordinates of the targe ...

Posted by **henrygao** on *Thu, 23 Sep 2021 07:07:48 -0700*

## Implementing decision tree with sklearn

Decision tree in sklearn
Module: sklearn.tree
tree.DecisionTreeClassifierClassification treetree.DecisionTreeRegressorRegression treetree.export_graphvizThe generated decision tree is exported to DOT mode for drawingtree.ExtraTreeClassifierHigh random version classification treetree.ExtraTreeRegressorHigh random version of regression tr ...

Posted by **WebMonkey** on *Wed, 22 Sep 2021 19:15:25 -0700*

## [computer graphics] clipping algorithm of straight line segment (source code + experimental report)

See the end of the text for the code
1. Purpose and content of the experiment
1.1 experimental purpose
Three line segment generation algorithms (DDA, improved Bresenham line drawing algorithm and improved midpoint line drawing algorithm) are realized through Python language, the core ideas of the three algorithms are deeply understood, ...

Posted by **bryanptcs** on *Tue, 21 Sep 2021 17:13:53 -0700*

## 3D reconstruction tool pcyly tutorial - how to search with KdTree

This tutorial is open source: GitHub Welcome fork
preface
In this tutorial, we will describe how to use KdTree to find the K nearest neighbors of a specific point or location, and how to find all neighbors within a radius specified by the user (random in this case).
Introduction to theory
kd tree or k-dimensional tree is a data struct ...

Posted by **abo28** on *Mon, 20 Sep 2021 17:12:59 -0700*

## Fundamentals of machine learning: the use of numpy

1, Numpy advantage
1. Introduction to ndarray
NumPy provides an N-dimensional array type ndarray, which describes a collection of "items" of the same type. Store with ndarray:
import numpy as np
# Create ndarray
score = np.array(
[[80, 89, 86, 67, 79],
[78, 97, 89, 67, 81],
[90, 94, 78, 67, 74],
[91, 91, 90, 67, 69],
[76, 87, 75, ...

Posted by **qrt123** on *Mon, 20 Sep 2021 11:24:57 -0700*

## Python - Decision Tree Classification Model Pruning

Catalog
1. Decision Tree Model Data Classification
2. Decision tree pruning alleviates over-fitting problems
*Common decision tree algorithms are ID3, C4.5, and CART. The ID3 algorithm, proposed by Quinlan, an Australian computer scientist, in 1986, is one of the classic decision tree algorithms. The ID3 algorithm uses information gain to s ...

Posted by **notsleepy** on *Sat, 18 Sep 2021 08:16:04 -0700*

## Detailed SVD and common Embedding applications

The reason for writing this article is that after embedding with SVD and deepwall in a recommended task, the effect of the model has been improved, and the application of SVD is beyond the knowledge of dimension reduction and there is a lot to think about, so some methods of SVD and embedding are summarized.
1. Singular Value Decomposition SVD ...

Posted by **EsOne** on *Sat, 18 Sep 2021 04:18:58 -0700*

## 7, Binary tree: the maximum depth of a binary tree

After reading this article, you can do the following two questions together:
104. Maximum depth of binary tree559.n maximum depth of fork tree
Force button topic link (opens new window)
Given a binary tree, find its maximum depth. The depth of the binary tree is the number of nodes on the longest path from the root node to the farthest ...

Posted by **lathifmca** on *Fri, 17 Sep 2021 21:36:26 -0700*

## Brian2_ Impulse neural network_ Neuron learning record

Impulse neural network is called the third generation neural network, which has higher biological reliability. SNN has always occupied the core position in the research of brain like science in recent years. When the performance is similar, the chip based on pulse neural network has lower power consumption, better stability and robustness than ...

Posted by **coverman** on *Thu, 16 Sep 2021 11:38:05 -0700*

## [hard HBase] HBase Optimization: pre partition / RowKey design / memory optimization / basic optimization

This article is right [hard big data learning route] learning guide for experts from zero to big data (fully upgraded version) HBase partial supplement.
1 high availability
In HBase, HMaster is responsible for monitoring the lifecycle of HRegionServer and balancing the load of regional server. If HMaster fails, the whole HBase cluster will fa ...

Posted by **svihas** on *Wed, 15 Sep 2021 19:31:12 -0700*