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Description: Visual Object Category Recognition
Robert Fergus Phd thesis. 2005
牛津大学博士学位论文。
研究内容为面向分类的目标识别。
主要研究内容为：
1、constellation model
2、加入location信息的改进的LDA model
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Size: 46159035 |
Author: eleyanz |
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Description: Visual Recognition: Computational Models and Human Psychophysics PhD thesis.
加州理工李菲菲的博士学位论文。
主要内容包括基于分类的目标识别研究：
1、costellation model
2、pLSA/LDA model
的目标识别研究。-Visual Recognition: Computational Models and Human Psychophysics PhD thesis. Caltech Professor Lee
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Author: eleyanz |
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Description: Visual Object Category Recognition
Robert Fergus Phd thesis. 2005
牛津大学博士学位论文。
研究内容为面向分类的目标识别。
主要研究内容为：
1、constellation model
2、加入location信息的改进的LDA model-Visual Object Category Recognition Robert Fergus Phd thesis. 2005 Doctoral Thesis University of Oxford. Research-oriented classification for object recognition. Main content: 1, constellation model2, adding location information to improve the LDA model
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Author: eleyanz |
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Description: bag-of-words by R. Fergus, L. Fei-Fei and A. Torralba
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Author: luwenhao |
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Description: Fergus, R 写的关于图像去抖动很好的一篇论文，作者有公开代码在他的主页上-one of Fergus, R s papers about removing camera shake from a single photograph,we can download it s source code from his homepage.
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Author: 葛浩宇 |
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Description: We present a method to learn and recognize object class
models from unlabeled and unsegmented cluttered scenes
in a scale invariant manner. Objects are modeled as flexible
constellations of parts. A probabilistic representation is
used for all aspects of the object: shape, appearance, occlusion
and relative scale. An entropy-based feature detector
is used to select regions and their scale within the image. In
learning the parameters of the scale-invariant object model
are estimated. This is done using expectation-maximization
in a maximum-likelihood setting. In recognition, this model
is used in a Bayesian manner to classify images. The flexible
nature of the model is demonstrated by excellent results
over a range of datasets including geometrically constrained
classes (e.g. faces, cars) and flexible objects (such
as animals).
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Size: 3409920 |
Author: Daria |
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Description: 图像反卷积
来自D. Krishnan, R. Fergus中提到的方法-image deconvolution
The Matlab functions in this directory solve the deconvolution problem in the
paper D. Krishnan, R. Fergus: "Fast Image Deconvolution using
Hyper-Laplacian Priors", Proceedings of NIPS 2009.
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Size: 2146304 |
Author: 李名 |
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Description: 本压缩文件是用matlab实现图像模糊恢复，代码超级详细，有实例。-The compressed file image blur restoration with matlab, the the super detailed code, there are instances.
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Size: 27481088 |
Author: 杨丽敏 |
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Description: 基于matlab模糊图像处理的一些m代码。主要有模糊核的计算 以及运动模糊图像的复原-M matlab code based on some fuzzy image processing. There are fuzzy core computing and motion-blurred image restoration, etc.
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Size: 29921280 |
Author: tanzou |
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Description: 该程序是Levin在2007年参会报告的，利用稀疏退卷积算法，对编码孔径相机进行图像和深度恢复的工作。-This package contains an implementation of the sparse deconvolution algorithm described in the paper:A. Levin, R. Fergus, F. Durand and W. T. Freeman:
Image and Depth a Conventional Camera with a Coded Aperture, SIGGRAPH 2007.
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Size: 5120 |
Author: clx |
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Description: Spectral Hashing Y. Weiss, A. Torralba, R. Fergus.
Advances in Neural Information Processing Systems, 2008. 所对应的示例的matlab代码，完整可运行
-Spectral Hashing
Y. Weiss, A. Torralba, R. Fergus.
Advances in Neural Information Processing Systems, 2008.
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Size: 17408 |
Author: dhx |
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Description: This package contains an implementation of the sparse
deconvolution algorithm described in the paper:
A. Levin, R. Fergus, F. Durand and W. T. Freeman:
Image and Depth a Conventional Camera with a
Coded Aperture, SIGGRAPH 2007.-This package contains an implementation of the sparse
deconvolution algorithm described in the paper:
A. Levin, R. Fergus, F. Durand and W. T. Freeman:
Image and Depth a Conventional Camera with a
Coded Aperture, SIGGRAPH 2007.
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Size: 717824 |
Author: kelly |
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Description: Spectral Hashing
Y. Weiss, A. Torralba, R. Fergus
Advances in Neural Information Processing Systems, 2008
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Size: 15360 |
Author: han123
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Description: 2006, Fergus, Removing Camera Shake from Single Image 代码(2006, Fergus, Removing Camera Shake from Single Image)
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Author: liyihan1020
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Description: 2006 ACM Removing Camera Shake From A Single Photograph( Rob Fergus)
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Size: 2961408 |
Author: owuchangyuo
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Description: 多智能体设置在机器学习中的重要性日益突出。超过了最近的大量关于深度的工作多agent强化学习，层次强化学习，生成对抗网络和分散优化都可以看作是这种设置的实例。然而，多学习代理人的存在这些设置使得培训问题的非平稳常常导致不稳定的训练或不想要的最终结果。我们提出学习与对手的学习意识（萝拉），一种方法，原因的预期。其他代理的学习。罗拉学习规则包括一个额外的术语，解释了在预期的参数更新的代理政策其他药物。我们发现，利用似然比策略梯度更新的方法，可以有效地计算萝拉更新规则，使该方法适合于无模型强化学习。这种方法因此规模。大量的参数和输入空间和非线性函数逼近。初步结果表明，遭遇两萝拉剂导致出现针锋相对针锋相对因此，在无限重复的囚徒困境中进行合作，而独立学习则没有。在这域，LOLA也得到更高的支出相对于朴素的学习者，并且对基于高阶梯度法的开发具有鲁棒性。应用于无限重复
便士匹配，只有萝拉剂收敛到纳什平衡.我们也将萝拉应用到网格世界任务中。一个嵌入式的社会困境使用深复发性政策。再次，通过考虑其他Agent的学习，LOLA代理商学会合作出于私利。(Due to the advent of deep RL methods that allow the study of many agents in rich environments, multi-agent reinforcement learning has flourished in recent years. However, most of this work considers fully cooperative settings (Omidshafiei et al., 2017; Foerster et al., 2017a,b) and emergent
communication in particular (Das et al., 2017; Mordatch and Abbeel, 2017; Lazaridou, Peysakhovich, and Baroni, 2016; Foerster et al., 2016; Sukhbaatar, Fergus, and others, 2016). Considering future applications of multi-agent RL, such as self-driving cars, it is obvious that many of these will be
yEqual Contribution only partially cooperative and contain elements of competition and selfish incentives)
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Author: 我去六六六
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Description: 运动模糊图像复原算法 matlab源码(matlab Motion blur image restoration)
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Size: 27480064 |
Author: allen-wqp |
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