<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Gone_HuiLin的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/Gone_HuiLin</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Gone_HuiLin]]></copyright><item><title><![CDATA[【浅谈网络舆情自动评判】]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126216689</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126216689</guid><author>Gone_HuiLin</author><pubDate>Sun, 07 Aug 2022 20:53:54 +0800</pubDate><description><![CDATA[随着互联网的全民普及以及互联网在全球范围内的互通，网络已经成为了人们生活的重要部分，人们可以在互联网上共享信息与资源，网络也成为信息快速传播的媒介与载体。但是互联网信息鱼龙混杂，琳琅满目，网络上一些不良信息给网络环境造成了污染并且会给个人、社会、国家带来危害，因此快速有效检测网络不良（垃圾）信息对网络环境的净化和文明和谐社会的构建将具有十分重要的意义。...]]></description><category></category></item><item><title><![CDATA[视频动作行为识别简述]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126216567</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126216567</guid><author>Gone_HuiLin</author><pubDate>Sun, 07 Aug 2022 20:37:09 +0800</pubDate><description><![CDATA[图像识别是对给定的图像进行分类，判断该图像属于预定义类别集合中的哪类。相对图像分类来说，图像目标检测更复杂的多，目标检测不仅要对图像中的目标进行识别，同时还要对其进行定位。类似地，视频动作行为检测相比视频动作识别来说更复杂，视觉行为识别是对已经分割好的视频片段进行动作行为分类，一般输入的视频是未经分割好的，模型预测时输入的是一段包括一种或者多种动作行为的视频片段，模型需要自动定位和识别出对应的动作以及其在原输入视频段中的起始位置。视频动作行为检测又可分为离线检测和在线检测，一般研究更多的是离线动作行为识。.]]></description><category></category></item><item><title><![CDATA[【读书、思考、写作】]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126216471</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126216471</guid><author>Gone_HuiLin</author><pubDate>Sun, 07 Aug 2022 20:27:41 +0800</pubDate><description><![CDATA[思考是对现有直接获取到信息进行甄别、提炼、归纳、总结，通过思考，可以形成举一反三的思维模式，形成批判性的思考方式，这样我们可以容易发现问题、提出问题、解决问题，甚至提出创新性的观点、解决方案，形成新的思想体系和新的解决问题的方法。如果将直接获取的原知识比作粗糙的谷粒，那么经过思考后提炼和总结的知识就是颗粒饱满、色彩光泽的精品谷粒。会思考、善于思考的人，生活也将给予他（她）更加丰厚的回报。......]]></description><category></category></item><item><title><![CDATA[计算机视觉发展和应用浅谈]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126216152</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126216152</guid><author>Gone_HuiLin</author><pubDate>Sun, 07 Aug 2022 20:07:55 +0800</pubDate><description><![CDATA[计算机视觉（Computer Vision）又称为机器视觉，顾名思义就是一门”教“计算机如何”看懂“世界的学科。计算机视觉从传统的计算机视觉技术发展到如今以深度学习技术为主线的视觉技术，本文将首先介绍传统计算机视觉中的特征提取方法、分类器的设计以及基于深度学习技术的自动特征提取及分类或回归技术，其次介绍一些典型的视觉应用及其使用的技术方案，然后介绍了视觉领域一些典型的工具（开发）库和的数据集，最后分析了计算机视觉领域面临的挑战以及对其未来进行展望。......]]></description><category></category></item><item><title><![CDATA[【人工智能入门预备知识】]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126215865</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126215865</guid><author>Gone_HuiLin</author><pubDate>Sun, 07 Aug 2022 19:46:33 +0800</pubDate><description><![CDATA[目前有不少高校，还积极响应国家大力提倡和发展人工智能，新增设了如人工智能之类的专业，计算机专业也成为了当前各种专业之中的香饽饽，水涨船高，竞争也更加激烈，整个AI领域充满了无尽的生机和活力。针对目前诸多国内高校本科就新开设的人工智能专业，我作为一个曾经也学习和了解过人工智能领域的研究生，在此针对人工智能专业入门应该掌握的基础知识和学习方法提一些建议，这可能有助于一些新手入门人工智能领域。...]]></description><category></category></item><item><title><![CDATA[学术研究和论文写作]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126213838</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/126213838</guid><author>Gone_HuiLin</author><pubDate>Sun, 07 Aug 2022 17:10:24 +0800</pubDate><description><![CDATA[我的学术研究方法与道路]]></description><category></category></item><item><title><![CDATA[fuzzy cmeans]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102673401</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102673401</guid><author>Gone_HuiLin</author><pubDate>Tue, 22 Oct 2019 09:56:43 +0800</pubDate><description><![CDATA[from __future__ import division, print_function
import numpy as np
from numpy.linalg import cholesky
import matplotlib.pyplot as plt
import skfuzzy as fuzz
import argparse
import sys
import random

#...]]></description><category></category></item><item><title><![CDATA[tensorflow生成对抗网络]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102673425</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102673425</guid><author>Gone_HuiLin</author><pubDate>Tue, 22 Oct 2019 09:56:30 +0800</pubDate><description><![CDATA[import tensorflow as tf
import numpy as np
import os
from tensorflow.examples.tutorials.mnist import input_data
from matplotlib import pyplot as plt

BATCH_SIZE = 64
UNITS_SIZE = 128
LEARNING_RATE = ...]]></description><category></category></item><item><title><![CDATA[mnist数据集保存为图片]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102673166</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102673166</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 22:07:55 +0800</pubDate><description><![CDATA[#coding: utf-8
from tensorflow.examples.tutorials.mnist import input_data
import scipy.misc
import os
import numpy as np

# 读取MNIST数据集。如果不存在会事先下载。
mnist = input_data.read_data_sets("MNIST_data/", one...]]></description><category></category></item><item><title><![CDATA[mxnet NDArray]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102673076</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102673076</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 22:02:35 +0800</pubDate><description><![CDATA[import mxnet as mx
import pickle as pkl
import numpy as np
import math

# create a 1-dimensional array with a python list
def demo1():
	a = mx.nd.array([1,2,3])
	b = mx.nd.array([[1,2,3], [2,3,4]])

...]]></description><category></category></item><item><title><![CDATA[python文件读写1]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672738</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672738</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 21:44:42 +0800</pubDate><description><![CDATA[# -*- coding: utf-8 -*-

# read txt file
def readTextFile(file):
	f = open(file, 'r')
	
	# 尽可能多的读取文件的内容，一般会将整个文件内容都会读取
	context = f.read() 
	print(context)
	
	f.close()
	
def readTextFileByLines(file...]]></description><category></category></item><item><title><![CDATA[tensorflow 2]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672573</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672573</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 21:35:29 +0800</pubDate><description><![CDATA[import tensorflow as tf
import numpy as np

def test1():
    #create data
    x_data=np.random.rand(100).astype(np.float32)
    y_data=x_data*0.1+0.3
    
    #create tensorflow structure
    Weights...]]></description><category></category></item><item><title><![CDATA[tesorflow 1]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672532</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672532</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 21:32:54 +0800</pubDate><description><![CDATA[# -*- coding: utf-8 -*-

import numpy as np
import tensorflow as tf
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import Lab...]]></description><category></category></item><item><title><![CDATA[mxnet mnist lenet]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672445</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672445</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 21:29:09 +0800</pubDate><description><![CDATA[import logging
import numpy as np
import mxnet as mx
import gzip
import os
import urllib
import urllib.request
import struct
	

# https://blog.youkuaiyun.com/weixin_38358654/article/details/79842612

def d...]]></description><category></category></item><item><title><![CDATA[mxnet mnist 3]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672424</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672424</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 21:27:59 +0800</pubDate><description><![CDATA[# -*- coding: utf-8 -*-
"""
Created on Thu Nov  8 14:32:42 2018

@author: lin
"""
import numpy as np
import os
import struct
import datetime
from tensorflow.examples.tutorials.mnist import input_data...]]></description><category></category></item><item><title><![CDATA[mxnet mnist 2]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672410</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672410</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 21:27:17 +0800</pubDate><description><![CDATA[import mxnet as mx
import numpy as np
import logging

logging.getLogger().setLevel(logging.INFO)
fname = mx.test_utils.download('http://archive.ics.uci.edu/ml/machine-learning-databases/letter-recogn...]]></description><category></category></item><item><title><![CDATA[mxnet mnist]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672373</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672373</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 21:24:54 +0800</pubDate><description><![CDATA[import numpy as np
import os
import urllib
import urllib.request
import gzip
import struct
import matplotlib.pyplot as plt
import mxnet as mx
import logging

from IPython.display import HTML
import c...]]></description><category></category></item><item><title><![CDATA[mxnet 线性回归 1]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672332</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102672332</guid><author>Gone_HuiLin</author><pubDate>Mon, 21 Oct 2019 21:23:12 +0800</pubDate><description><![CDATA[import mxnet as mx
import numpy as np

from mxnet import autograd, nd
from mxnet import gluon
from mxnet import init
from mxnet.gluon import nn
from mxnet.gluon import data as gdata
from mxnet.gluon ...]]></description><category></category></item><item><title><![CDATA[keras Classifier 分类]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102312899</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102312899</guid><author>Gone_HuiLin</author><pubDate>Mon, 07 Oct 2019 16:30:07 +0800</pubDate><description><![CDATA[import numpy as np
np.random.seed(1337)  # for reproducibility
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.optimizers import RMSprop
import matplotlib.py...]]></description><category></category></item><item><title><![CDATA[keras Regressor 回归]]></title><link>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102312102</link><guid>https://blog.youkuaiyun.com/Gone_HuiLin/article/details/102312102</guid><author>Gone_HuiLin</author><pubDate>Mon, 07 Oct 2019 16:15:25 +0800</pubDate><description><![CDATA[import numpy as np
np.random.seed(1337)  # for reproducibility
from keras.models import Sequential
from keras.layers import Dense
import matplotlib.pyplot as plt # 可视化模块

import tensorflow as tf
impo...]]></description><category></category></item></channel></rss>