PCNN

基本解釋

In this paper，a new method of image compression using PCNN and RLE is put forward to overcome the limitation of RLE.
提出了一種由PCNN和行程編碼結合的圖像壓縮方法，來克服行程編碼的缺陷。
This thesis makes an attempt on the application of PCNN for medical image segmentation audaciously and tries to open a new way for image segmentation.
本文對脈沖耦合神經(jīng)網(wǎng)絡方法在各類醫(yī)學圖像分割中的應用進行了大膽嘗試，為醫(yī)學圖像分割提供了新的思路。
Simulation experiment shows that the improved PCNN has better robustness and can realize the adaptive segmentation of irregular image.
仿真實驗表明，改進后的算法能夠實現(xiàn)不規(guī)則圖像的自適應分割，魯棒性較好。
In this paper,a new method of low contrast image enhancement is presented based on PCNN and LR models in conjunction with characteristics of human visual consciousness.
針對低對比度圖像,結合人眼視覺神經(jīng)系統(tǒng)的感知特性,提出了一種基于PCNN與LR模型的圖像增強方法。
The entropy series and neurons firing series of the image obtained by feeding the spectrogram into PCNN were used as the characteristics of emotion speech for emotion recognition.
該方法將語音轉化為語譜圖后輸入到PCNN，得到輸出圖像的神經(jīng)元點火序列及其熵序列作為語音情感的特征，利用其特征實現(xiàn)語音情感識別。