搜索资源列表
MOD
- MOD算法是经典的字典学习算法，他能适应各种信号如图像、声音、机床振动等的稀疏表示-MOD algorithm is the classic dictionary learning algorithm, he can adapt to a variety of signals, such as sparse image, sound, vibration or the like, said machine tool
sparse_learning
- 一种贝叶斯学习算法，可以实现的广义版本SBL和集中学习稀疏-Bayesian learning algorithm can achieve generalized version of SBL and focus on learning sparse
linear_autoencoder
- 自动编码线性解码器主要是考虑到稀疏自动编码器最后一层输出如果用sigmoid函数，由于稀疏自动编码器学习是的输出等于输入，simoid函数的值域在[0,1]之间，这就要求输入也必须在[0,1]之间，这是对输入特征的隐藏限制，为了解除这一限制，我们可以使最后一层用线性函数及a z-Automatic linear encoder decoder mainly on account of sparse autocoder last layer output if sigmoid function,
slotest
- 通过slo稀疏重构算法对lena.bmp图片进行压缩重构的一个实例，适合入门学习压缩感知- U901A u8FC7slo u7A00 u758F u91CD u6784 u7B97 u6CD5 u5BF9lena.bmp u56FE u7247 u8FDB u884C u538B u7F29 u91CD u6784 u7684 u4E00 u4E2A u5B9E u4F8B uFF0C u9002 u5408 u5165 u95E8 u5
SAE_DBN_CNNToolbox
- 多种深度学习框架，主要包括堆栈稀疏自动编码器，深信度网络，卷积神经网络等。对于灰度图像和高维图像，展现非常强大的学习性能。-A variety of deep learning framework, including automatic stack sparse encoder, is convinced of the network, convolution neural networks. For grayscale images and high-dimensional image, s
BSBL-FM-master
- 基于贝叶斯学习方法的块稀疏信号压缩感知算法-A fast implementation of the Block Sparse Bayesian Learning algorithm
EA-SRC
- 利用超限学习机（ELM）和稀疏表示(SRC)进行图像分类。Matlab完整源码。-Extreme learning machine and adaptive sparse representation for image classification
CodesPAMI2015
- 这是关于稀疏字典学习用于人脸识别图像处理的文章，里面是对应的算法代码-This is an article about sparse dictionary learning for face recognition image processing, which is the corresponding algorithm code
PolSAR-ship-detection
- 基于稀疏表示的极化SAR舰船目标检测，有益于学者学习-Polarization SAR ship target detection based on sparse representation, is conducive to academic study
LCksvd
- 经典LCKSVD算法的实现，稀疏编码与字典学习的重要过程。-Classical LCKSVD algorithm implementation, sparse coding and dictionary learning an important process.
CSR_Denoising
- 该算法首先通过字典学习得到含噪图像的冗余字典，然后对相似的图像块进行聚类构成块群，并通过迭代收缩和L1正则化约束，对同类的图像块在字典上进行稀疏表示，以达到降噪的目的。实验结果表明，在常规的图像处理上，本文提出的算法能较好的保留图像的结构信息，与K-SVD和BM3D等现有的流行算法相比，具有更高的峰值信噪比（PSNR）-It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the
KSVDdenoise
- ksvd 去噪，通过字典学习后得到的字典，对图像进行稀疏分解，从而达到去噪效果。(Ksvd denoising, through the dictionary learning to obtain the dictionary, the image sparse decomposition, so as to achieve denoising effect.)
incrementallearning_LCKSVD_shared
- 单幅图像超分辨处理 深度学习 稀疏表示 字典学习(Single image, super-resolution processing, depth learning, sparse representation, dictionary learning)
ksvdbox13
- 奇异值分解算法，用于字典的学习和构建，可以很好的对数据进行降维和稀疏化。(Singular value decomposition algorithm for the study and construction of the dictionary, can be a good data for dimensionality and thinning.)
K-SVD
- 稀疏编码和字典学习算法，正交匹配追踪算法获得稀疏表示稀疏，ksvd用来学习字典(Sparse coding and dictionary learning algorithm, orthogonal matching tracking algorithm to obtain sparse sparse, ksvd used to learn the dictionary)
SRC
- 这是文章《Sparse Representation For Computer Vision and Pattern Recognition》的对应的稀疏表示代码，非原创，转载而来，供大家交流学习。(This is the code of SRC algorithm,and it's reproduced from others.)
KSVD
- 一种在matlab环境下的计算稀疏表示的学习字典的算法(A learning dictionary algorithm for computing sparse representation in Matlab environment)
BPFA_Denoising
- 利用非参数贝叶斯字典学习模型进行图像稀疏表示(use non-parametric-bayesian-dictionary-learning-for-sparse-image-representations)
107215802AnalysisKSVD
- 实现图像的稀疏编码，采用k-svd进行字典学习，omp算法进行稀疏表示系数的计算，内附有去噪例子(To achieve the image sparse coding, using K-SVD dictionary learning, OMP algorithm for sparse representation of the calculation of factors, with examples of denoising)
SB2_Initialisation
- 基于稀疏贝叶斯学习算法预测理论，利用稀疏贝叶斯的进行概率预测(Sparse bayesian learning)