彩信

【实例简介】

Deep Learning With Python_中文版 --本书由Keras之父、现任Google人工智能研究员的弗朗索瓦?肖莱（Franc?ois Chollet）执笔，详尽介绍了用Python和Keras进行深度学习的探索实践，包括计算机视觉、自然语言处理、产生式模型等应用。书中包含30多个代码示例，步骤讲解详细透彻。(Chinese Version - This book is written by Franc OIS Chollet, the father of Keras and current researcher of Google Artificial Intelligence. It introduces in detail the exploratory practice of in-depth learning with Python and Keras, including computer vision, natural language processing, production model and other applications. The book contains more than 30 code examples with detailed steps.)

用树莓派读取温湿度传感器，光照传感器，气压传感器读取数据

使用matlab进行图像去雾，有助于帮助刚入门的图像小白学习matlab图像处理(Matlab image defogging, helpful to help beginners learning image white matlab image processing)

滑窗计算刀具磨损量，拟合刀具边界，自动计算磨损量(sliding window based tool wear calculation)

说明：  实现强化学习，完成人工智能，实现机器学习，掌握分类算法(Realize reinforcement learning, artificial intelligence, machine learning and deep learning)

频繁项集挖掘算法FPGrowth用Python实现(Python implementation of frequent itemsets mining algorithm)

GMM聚类实现，利用jupybook实现出来，可以看算法的实现原理。(GMM clustering implementation, using jupybook realization, can see the implementation principle of the algorithm.)

基于机器学习的认知无线电频谱感知,机器学习的认知无线电频谱感知(Based on machine learning cognitive radio spectrum sensing, machine learning, cognitive radio spectrum sensing)

说明：  针对图像亮度不均匀问题，Li Tao与2005年提出的这个算法。其主要用于提升再低照度或者不均匀光照条件下拍摄到的图像亮度。该算法主要由两部分构成：自适应亮度增强模块和自适应对比度增强。(Li Tao and this algorithm proposed in 2005 for the problem of uneven image brightness. It is mainly used to enhance the brightness of images captured under low illumination or uneven illumination. The algorithm is mainly composed of two parts: adaptive brightness enhancement module and adaptive contrast enhancement.)