No self-introduction
Loading
Profile
Follow
codes (3)
BM4D image sequence denoising method matlab code
4.0
Application background With the popularization of various digital instruments and digital products, image and video have become the most common information carriers in human activities, they contain a large amount of information, and become the main way to obtain the original information of the outside world. However, in the process of image acquisition, transmission and storage, image quality is often affected by noise, and image preprocessing algorithm is directly related to the subsequent image processing, such as image segmentation, object recognition, edge extraction, and so on, it is necessary to obtain high quality digital images. Therefore, noise reduction processing has been a hot spot in the research of image processing and computer vision.The ultimate goal of image denoising is to improve the image quality and solve the problem of the image quality degradation due to noise interference. The image quality can be effectively improved by the denoising techni
yang123jx 1 0
1
Toolbox tensor tensor toolbox
4.0
Application background Zhang Liang (tensor) theory is a branch of mathematics, it has important applications in mechanics. The term tensor is derived from mechanics, which is initially used to represent the stress state of each point in the elastic medium, and later the tensor theory developed into a powerful mathematical tool for mechanics and physics. Tensor is important, because it can satisfy all the physical laws must be independent of the choice of the coordinate system. Tensor concept is a generalization of vector concept, vector is a first order tensor. Tensor is a linear function of the linear relationship between the number of vector, scalar and other tensor. Key Technology A matlab tensor analysis toolbox, containing commonly used tensor calculation functions and tensor decomposition functions, such as Tucker decomposition, CP decomposition, tensor multiplied by vector, matrix, tensor and other basic algorithms, as well as the use of t
yang123jx 0 0
1
Learning deep character recognition code -Hinton classic
no vote
Application background Character recognition can be applied in many fields, such as reading, translation, literature retrieval, letters and parcels sorting, manuscript editing and proofreading, a large number of statistical statements and cards the collection and analysis, a statistical summary of the bank check processing, commercial invoice, commodity code identification, goods warehouse management, and water, electricity, gas, rent, insurance and other personal expenses of collection of business of a large number of credit card of the automatic processing and a typist in an office work of local automation and so on. As well as document retrieval, all kinds of documents recognition, convenient user to enter information quickly, improve the work efficiency of all walks of life. Key Technology Data can be converted to low-dimensional codes by training a multilayer neural High-dimensionalWith a small central layer to reconstruct high-dimensional i
yang123jx 0 0
1
No more~
Follows0
Fans0