资源列表
cnn
- 卷积神经网络(CNN),TensorFlow框架下运行,基于MNIST手写体数据集,可直接运行(Convolutional Neural Network (CNN), run under TensorFlow framework, can run directly based on MNIST handwritten dataset)
Artificial potential field method
- 应用改进的人工势场法进行机器人的路径规划,加入避障功能。(The improved artificial potential method is applied to the path planning of the robot, and the obstacle avoidance function is added.)
Unit_A
- 通过红外摄像头控制小车避障,到达指定的目的地,并在过程中扫描地形(control the car to avoid obstacle by using laser)
深度学习-李宏毅
- 台湾大学李宏毅老师的深度学习资料,讲解详细,适合初学者学习使用(Deep Learning Tutorial)
深度学习机器学习入门进阶精品名师视频课程
- (23套)深度学习+(48套)机器学习入门+进阶精品名师视频课程((23 sets) deep learning + (48 sets) machine learning + video course of advanced Elite Teachers)
人工智能:一种现代方法(第2版).pdf
- 人工智能:一种现代方法:帮你更好的理解人工智能,系统的学习未开科技人工智能,走进AI时代。(Artificial Intelligence: A Modern Approach: Helping You to Understand Artificial Intelligence Better, Systemic Learning Without Artificial Intelligence, Into The AI Age.)
firefly algorithm
- 实现萤火虫算法,实现了一篇论文,主要是优化算法,用于寻找多目标时的最优值,效果比较理想,可以通过动图展示出来(Firefly algorithm to achieve)
ELM分类器
- ELM是基于深度学习的分类器,运算速度快。 在B_data.m里导入待分类矩阵B.mat(1-n列为特征值,n列为标签);运行B_data.m;再打开fuzzyEn_main.m并运行即可。(ELM is based on depth learning classifier, computing speed. In B_data.m imported matrix to be classified B.mat (1-n as eigenvalues, n as a label); Run B
libs
- 用矩阵补全或张量补全的方法,对缺失数据进行重构(matrix completion or tensor completion ,to reconstruct the missing data)
深度学习python代码
- 深度学习代码,Python,自己觉得还可以,愿对你有所帮助。(Deep study code, Python, feel that you can, may be helpful to you.)
bp神经网络
- 两个bp神经网络的预测程序(含有详细注释)。(Prediction program for two BP neural networks (detailed notes))
bp神经网络
- 根据Ecotect 模拟的12种不同的建筑形状进行能量分析,数据集包括768个样本和8个特征属性,旨在预测房屋的热负荷和冷负荷。BP神经网络(According to the 12 different building shapes simulated by Ecotect, we carry out energy analysis. The dataset includes 768 samples and 8 characteristic attributes, aiming at predi