资源列表
Deep Learning with Python-Manning
- 深入学习Python介绍领域的深入学习使用Python语言和强大的Keras图书馆。通过keras创造者和谷歌人工智能研究者弗兰?ois Chollet写的,这本书让你了解通过直观的解释和实例。您将探索具有挑战性的概念和实践与计算机视觉,自然语言处理和生成模型的应用程序。当你完成学业的时候,你将具备在自己的项目中应用深度学习的知识和动手能力。(Deep Learning with Python introduces the field of deep learning using the Pyt
aiu.rar
- 中国科学院李德毅院士在北京航空航天大学关于不确定性人工智能的讲座PPT。,Uncertainty Artificial Intelligence Seminar PPT
PIDbook
- PID仿真参考书,关于神经网络等方面的书,应用广泛。希望大家积极下载。-PID simulation of reference books, such as neural networks on the books, a wide range of applications. Hope that we actively download.
Simscape-HEV-Series-Parallel-18.1.2.4
- sim scape hev series parallel arrangement
MATLAB-SHENJINGWANGLUO-CASE
- 这是关于神经网络的有关案例分析的MATLAB资料,案例里边有相关程序,供大家使用-This is the information about the case on MATLAB neural network analysis, case inside there procedures for everyone to use
Packing
- 圆形 packing 问题的拟物拟人算法vc++实现 -vc++ source of packing
system-of-K-Means-and-its-plus
- 实现了k-means极其改良算法,提高了聚类的精度。内附详细文字说明及源代码,配有图形界面演示。-The implementation of k-means algorithm and its plus.Improve the accuration of clustering.The document and source are both added.
ANN
- 这是一个基于人工神经网络的数字识别系统的程序,包括数字训练库,采用Visual C++实现。-This is an artificial neural network-based digital identification system procedures, including the number of training database, using Visual C++ implementation.
helios-base
- 日本helios改良过的底层代码,版本为3.11以上-Japan helios improved over the underlying code, version 3.11 or more
Matlab-neural-network-analysis
- 《matlab神经网络30个案例分析〉书的配套程序,对于学习神经网络有帮助!-30 cases of the Matlab neural network analysis book supporting the program, learning neural network!
Simple Demo
- 人搜索 依赖 在python3.7 MacOS 10.14.6下测试 ——python包 ——opencv-python ——tb-nightly -torch>= 1.0 下载weights 从这里下载,密码:qscx 下载后,将权重放到文件夹 person_search_demo/weights中 测试 cd <指向此floder>的路径 python search 结果将保存在输出文件夹中 训练 您可以直接使用原始的YOLO代码进行培训。
Simulated-Annealing-solving-TSP
- 此段程序是用模拟退火思想解决旅行商TSP问题,有详细步骤说明。-This program solves the Traveling Salesman Problem(TSP) using an intelligent algorithm of the simulated annealing,which detail steps are explained.