Http://www.matlabfan.com/thread-646-1-1.html
Author]Edited by Hu Xiaofeng and Zhao Hui
[Press]People's post and telecommunications Publishing House
【Contents]This book systematically introduces the basic principles, typical methods, and practical technologies of image processing and recognition. The book consists of 12 chapters, Chapter 1st ~ Chapter 2 is the basic content of image processing and recognition
Since the 70 's, with the development of cognitive psychology itself, there have been some important changes in the orientation of cognitive psychology in the study of pattern recognition. Some cognitive psychologists continue to study the characteristics of computer and human identification patterns based on the hypothesis of physical symbology, while others turn to the idea of neural networks to study the problem of
pooling, unexpectedly can through such a boundary information, really do not understand why. This makes people think about why this operation is so pooling and omnipotent. Someone asked this question: what is the use of the pooling layer of the CNN network, what the max pooling and average pooling in the image classification do to the features, and what is the result? But it seems to come to the conclusion that this is a result of a pat on the head ... This systematic analysis of the paper "a t
http://www.dengfanxin.cn/?p=403Original address
I have translated the main parts of an important work on object detection, sppnet, in the paper. Sppnet's original intention is very clear, is that the network to the size of the input is more flexible, analysis to the convolutional network size is not required, the requirements of the fixed size is entirely from the whole connection layer, so the use of spatial pyramid pooling method to connect the two, The important contribution of sppnet
';'*. * '}, 'Load image'); If isequal (filename, 0) | isequal (pathname, 0) errordlg ('unselected file', 'error'); return; else file = [pathname, filename]; global S % sets a global variable S and saves the initial image path so that subsequent restoration operations S = file; X = imread (File ); set (handles. axes1, 'handlevisibility ', 'on'); axes (handles. axes1); imshow (x); handles. IMG = x; guidata (hobject, handles); End
In fact, the above code is very fixed, so you just need to copy
Article Description: brand recognition can be derived from different forms of expression. It can be auditory, like the Nokia Classic ringtones. It can also be visual: a variety of design elements from the most intuitive trademarks and deeper inside the product.
Brand recognition can be derived from different forms of expression. It can be auditory, li
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