一本将基于AP传播算法的半监督聚类的算方法书.对于聚类研究的很有帮助-The Uncapacitated Facility Location Prob- lem (UFLP) is one of the most widely stud- ied discrete location problems, whose appli- cations arise in a variety of settings. We tackle the UFLP using probabilisti

Otsu算法步骤如下： 设图象包含L个灰度级(0,1…,L-1)，灰度值为i的的象素点数为Ni ，图象总的象素点数为N=N0+N1+...+N(L-1)。灰度值为i的点的概率为： P(i) = N(i)/N. 门限t将整幅图象分为暗区c1和亮区c2两类，则类间方差σ是t的函数： σ=a1*a2(u1-u2)^2 (2) 式中，aj 为类cj的面积与图象总面积之比，a1 = sum(P(i)) i->t, a2 = 1-a1 uj为类cj的均值，u1 = sum(i*P(

sum pooling, max pooling, average pooling,三种 Feature Coding pooling方法-sum pooling, max pooling, average pooling, three kinds of " Feature Coding" pooling method