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14篇 您的检索式:作者名="Mahoor"
    题名 作者 年代 出处 被引量
1Fast im- age blending using watersheds and graph cuts显示文摘Gracias N Mahoor M Negahdaripour S 2009Image and Vision CompJting2009,27,5:1
2Fast image blending using watersheds and graph cuts显示文摘Gracias N Mahoor M Negahdaripour S 2009Image and Vision Computing2009,27,5:1
3Face recognition based on 3D ridge images obtained from range data显示文摘Mohammad H. Mahoor Mohamed Abdel-Mottaleb 2008Pattern Recognition2008,,3:1
4Fastimage blending using watersheds and graph cuts 显示文摘Gracias N Mahoor M Negahdaripour S 2009Image and Vision Computing (S0262-8856)2009,27,5:1
5DISFA:a spontaneous facial action intensity database显示文摘Mavadati S M Mahoor M H Bartlett K 2013IEEE Trans on Affective Computing2013,4,2:1
6Face recognition based on 3D ridge images obtained from range data显示文摘Mohammad H Mahoor MohamedAbdel-Mottaleb 2009Pattern Recognition2009,,:1
7PCA-based di- ctionary building for accurate facial expression recogni- tion via sparse representation显示文摘Mohammadi M Fatemizadeh E Mahoor M 2014Journal of Visual Com- munication and image Representation2014,25,5:1
8Fast imageblending using watersheds and graph cuts显示文摘Gracias N Mahoor M Negahdaripour S 2009Image and VisionComputing2009,27,5:1
9NonverbalSocial Withdrawal in Depression: Evidence from manualand automatic analysis 显示文摘GIRARD J M COHN J F MAHOOR MH 2014Image Vis Comput2014,32,10:1
10Human activity recognition using multi-features and multiple kernel learning显示文摘Althloothi S Mahoor MH Zhang X 2014Pattern Recognition2014,47,5:1
11Non-neg- ative sparse decomposition based on constrained smoothed t0 norm 显示文摘Mohammadi M R Fatemizadeh E Mahoor M H 2014IEEE Transactions on Signal Processing2014,100,7:1
12Fast Image Blending Using Watersheds and Graph Cuts显示文摘Gracias N Mahoor M Negahdaripour S 0,,05:1
13PCAbased dictionary building for accurate facial expression recognition via sparse representation显示文摘Mohammadi M R Fatemizadeh E Mahoor M H 2014Journal of Visual Communication and Image Representation2014,25,5:1
14形态学使机器人理解人类指令显示文摘现如今,越来越多的机器人在物理表现上与人类相接近,确保他们做出的决定以及如何行为与人类价值观具有一致性变得至关重要。为了实现这一目标,机器人需要了解人类所发出指令背后的真实意图。在本文中,Zahra Mahoor Jack Felag Josh Bongard 2018机器人产业2018,0,1:0
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