By Yide Ma, Kun Zhan, Zhaobin Wang
Purposes of Pulse-Coupled Neural Networks explores the fields of snapshot processing, together with photograph filtering, photo segmentation, photo fusion, snapshot coding, photo retrieval, and biometric reputation, and the position of pulse-coupled neural networks in those fields. This booklet is meant for researchers and graduate scholars in man made intelligence, trend attractiveness, digital engineering, and machine technological know-how. Prof. Yide Ma conducts examine on clever details processing, biomedical photo processing, and embedded method improvement on the institution of knowledge technological know-how and Engineering, Lanzhou college, China.
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Additional resources for Applications of Pulse-Coupled Neural Networks
2 Image Segmentation Using Entropy and Histogram Usually, when the gray-level distribution of objects in an image diﬀers from that of the background signiﬁcantly, two peaks may appear in its histogram and generally the more obvious trough is selected as the preferable threshold. 1 Traditional Methods and Evaluation Criteria 29 the image, there always exist a few and unobvious troughs in the histogram, which makes it diﬃcult to get a reasonable threshold. Moreover, the trough is determined manually from the histogram, by which it is diﬃcult to ﬁnd out an ideal threshold.
In this section, the principle of the irregular segmented region coding and decoding by means of these orthonormal basis-functions is mainly investigated in detail. The ISRCCBP will be more suitable for the segmented regions and natural edge of objects in the original image. It much better matches the HVS  and will not only be able to achieve higher compression ratios but also obtain the reconstructed image with better quality. Principle and experimental results based on the ISRCCBP will be presented in next section.
N and cj,j = 0. 9) where, N1 = ||φ1 − d1,0 ϕ0 ||, d1,0 is equal to < φ1 , ϕ0 > because φ1 and ϕ0 are orthonormal. 10) < φn , ϕi > ϕi || 1
Applications of Pulse-Coupled Neural Networks by Yide Ma, Kun Zhan, Zhaobin Wang