At present，The latest verion of offical OpenCV is 4.5.2。 In this blog, I introduce how to compile OpenCV from source code and enable GPU/CUDA support - GPU: Tesla V100 - CUDA: 11.0 - CUDA Capability: 7.0 (corresponding to GPU Tesla V100) - OS: Ubuntu 20.04 Dow…
对于一个全新的Ubuntu20.04系统，我们将使用这个脚本安装GPU驱动、CUDA11.0、cudnn11.2、Python、Pytorch和Opencv。 注意，请首先手动下载cudnn11.2 地址：https://developer.nvidia.com/rdp/cudnn-download 注意，请首先手动下载cudnn11.2 地址：https://developer.nvidia.com/rdp/cudnn-download 注意，请首先手动下载cudnn11.2 地址：https:…
这篇文章介绍了我近期的工作，一个端到端的手势识别模型。 识别手势在智能交互系统领域是一个基本研究课题。能够快速识别出用户的手势并做出反应对智能交互系统的用户体验有很重要的作用。手势识别在安全、K12教育、工业领域都有广泛的应用。 本文介绍一个端到端的手势识别系统的模型。这个模型的输入是一张$240*320$ 的 RGB 图像，输出是6种预…
In this article, we talk about Particle Swarm Optimization. In last post, we talked Computational tools, including Cellular automata Ant Colony Optimization Particle Swarm Optimization Particle Swarm Optimization Originally intended to simulate bird flocks and…
Intelligence <- Social behavior Intelligence can emerge from social interaction. Emergent behaviour – when a group behaves in ways that were not ”programmed” into its members Swarm intelligence simulated social interaction emergent collective intelligence i…
EC is parallel search (many balls in the landscape). Want to prevent all individuals from converging to the same solution (premature convergence – a common problem) The task of mutation is to prevent this – to maintain diversity in the population. To inject ne…
From course, I learned Evolutional Computing. Evolutionary computing (EC) population method Used for problems where the task is to maximize some measure of success Same family of problems as in RL, but very different methods Methods inspired by genetics, natur…
Let us firstly revisit completive learning and SOFM A node position (in the input space) is its weight vector, i.e. nodes move around in the same space as the data. Purpose of unsupervised learning is (usually) to cluster for classification, or for modelling d…
In this note, we are going talk about Deep Learning very briefly. RBFNs are feedforward networks, where: The hidden nodes (the RBF nodes) compute distances, instead of weighted sums. The hidden layer activation functions are Gaussians (or similar), instead of …
To learn from unlabeled data (only inputs, no target information). Most often for classification. Requires that class membership can be detected by structural properties (features) in the data, and that the learning system can be fund these features. Following…
