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9篇 您的检索式:作者名="Saputro"
    题名 作者 年代 出处 被引量
1Expert system for agricultural aerial spray drift 显示文摘Saputro S Smith D B Shaw D R 1991Transactions of the ASAE1991,34,3:1
2Enhancement of myocardial boundary tracking using wavelet-based motion estimation 显示文摘Saputro A H Mustafa M M Hussain A 2011Journal of Information and Computational Science2011,8,10:1
3Fogging with a mixture of Basudin 60 EC and sunshine to control Ceratovacuna lanigera Zehntner in the Camming sugar manufacturing region 显示文摘Saputro S E Trijantro B Harhap R M 1995Berita Perkebunan Gula Indones1995,,12:1
4A survey of routing protocols for smart grid communications显示文摘SAPUTRO N AKKAYA K ULUDAG S 2012Computer Networks2012,56,11:1
5A survey of routing proto- cols for smart grid communications显示文摘Saputro N Akkaya K Uludag S 2012Computer Networks2012,56,11:1
6Optimisation and validation of the microwave- assisted extraction of phenolic compounds from rice grains显示文摘Setyaningsih W Saputro I E Palma K 2015Food Chemistry2015,169,1:1
7A survey of routing protocols tbr smart grid communications显示文摘Saputro N Akkaya K Uludag S 2012Computer Networks2012,56,11:1
8On preserving user privacy in Smart Grid advanced metering infrastructure applications显示文摘Nico Saputro Kemal Akkaya 2014Security Comm Networks2014,,1:1
9Apex Frame Spotting Using Attention Networks for Micro-Expression Recognition System显示文摘Micro-expression is manifested through subtle and brief facial movements that relay the genuine person’s hidden emotion.In a sequence of videos,there is a frame that captures the maximum facial differences,which is called the apex frame.Therefore,apex frame spotting is a crucial sub-module in a micro-expression recognition system.However,this spotting task is very challenging due to the characteristics of micro-expression that occurs in a short duration with low-intensity muscle movements.Moreover,most of the existing automated works face difficulties in differentiating micro-expressions from other facial movements.Therefore,this paper presents a deep learning model with an attention mechanism to spot the micro-expression apex frame from optical flow images.The attention mechanism is embedded into the model so that more weights can be allocated to the regions that manifest the facial movements with higher intensity.The method proposed in this paper has been tested and verified on two spontaneous micro-expression databases,namely Spontaneous Micro-facial Movement(SAMM)and Chinese Academy of Sciences Micro-expression(CASME)II databases.The proposed system performance is evaluated by using the Mean Absolute Error(MAE)metric that measures the distance between the predicted apex frame and the ground truth label.The best MAE of 14.90 was obtained when a combination of five convolutional layers,local response normalization,and attention mechanism is used to model the apex frame spotting.Even with limited datasets,the results have proven that the attention mechanism has better emphasized the regions where the facial movements likely to occur and hence,improves the spotting performance.Ng Lai Yee Mohd Asyraf Zulkifley Adhi Harmoko Saputro Siti Raihanah Abdani 2022Computers, Materials & Continua2022,,12:0
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