搜索资源列表
MRF-benchmarks
- 马尔科夫随机场(MRF)基准，包括MRF库和验证图像-code for all the benchmarks, including the MRF library and imageLib
MRF-benchmarks
- markov random fields的各类优化算法及应用Optimization methods included: 1) ICM 2) Graph Cuts 3) Max-Product Belief Propagation 4) Sequential tree-reweighted message passing (TRW-S) Applications include: (1)binary (2)denoise (3)stereomatch (
efficient_subpixel_registration
- 实现基准图和实时图之间亚象素级的匹配,做景象匹配的朋友可以看看.-Implementation benchmarks and real-time map map between the matching sub-pixel class, to do scene matching friends can see.
v1s-0.0.5.tar
- V1S 0.0.5 -- Basic V1-Like (simple cells) Object Recognition System -Why is Real-World Visual Object Recognition Hard? (2008) Pinto N, Cox DD, DiCarlo JJ PLoS Computational Biology Vol. 4, No. 1, e27 doi:10.1371/journal.pcbi.0040027 Es
Visual-software-choice
- 近十年来，NI在机器视觉和图像处理方面一直是领导者。NI视觉软件包含于两个软件一NI视觉开发模 块和用于自动检测的NI视觉生成器(NI Vision Builder for Automated Inspection)。视觉开发模块包含 数以白计的视觉函数，NI LabVIEW, NI LabWindows/CVI, C/C++、或Visual日asic可以使用这些函数 来编程创建功能强大的视觉检测、定位、验证和测量应用程序。Vision日uilder AI是一个交4_式的软件环
Discriminativemodelsformulticlasobject
- Many state-of-the-art approaches for object recognition reduce the problem to a 0-1 classifi cation task. Such re- ductions allow one to leverage sophisticated classifi ers for learning. These models are typically trained independentl
ug-automotive-die-aided-
- ug汽车冲模辅助设计工具*,可以自动添加键槽，基准快等你给奶奶给你给你给你-ug automotive die-aided design tool plug-in, you can automatically add the keyway, benchmarks and fast you give to your grandmother gave you give your
DeepLearnToolbox
- 关于深度学习的比较好的代码参考资料，包括CAE，CNN,DBN,NN,SAE等基准程序-Depth learning about good code references, including CAE, CNN, DBN, NN, SAE and other benchmarks
nipsw12poster
- 候晓迪的经典论文A Meta-Theory of Boundary Detection Benchmarks，做边缘检测很有用哦-one of Hou Xiaodi s papers A Meta-Theory of Boundary Detection Benchmarks
TrafficDetection-master
- 一种综合多种算法的车辆检测和追踪方法，运行时间较长，但效果很棒(We implement a system for vehicle detection and tracking from traffic video using Gaussian mixture models and Bayesian estimation. In particular, the system provides robust foreground segmentation of moving vehicles