Titlebook: Advances in Artificial Intelligence; 17th Conference of t Oscar Luaces ,José A. Gámez,Emilio Corchado Conference proceedings 2016 Springer

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書(shū)目名稱(chēng)Advances in Artificial Intelligence影響因子(影響力)




書(shū)目名稱(chēng)Advances in Artificial Intelligence影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Advances in Artificial Intelligence網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Advances in Artificial Intelligence網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Advances in Artificial Intelligence被引頻次




書(shū)目名稱(chēng)Advances in Artificial Intelligence被引頻次學(xué)科排名




書(shū)目名稱(chēng)Advances in Artificial Intelligence年度引用




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書(shū)目名稱(chēng)Advances in Artificial Intelligence讀者反饋




書(shū)目名稱(chēng)Advances in Artificial Intelligence讀者反饋學(xué)科排名

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https://doi.org/10.1007/978-3-642-68178-3. In this paper, we address the speaker diarization problem as a visual speaker re-identification issue with a special emphasis on the analysis of different shot types. We propose two approaches that makes use of convolutional neural networks (CNN) and biometric traits for keyframe extraction. Exper

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Simon Bailey,Jeannette Parkes,Alan Davidsonhave followed the same trend. However, most of classification methods are not performed on-line. Moreover, data streams produce huge amounts of data and the available processing resources may not be sufficient. This work-in-progress paper proposes an algorithm for Multi-label Classification applicat

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Lorenzo Lorusso,Simone Venturini fairly comparing the performance of these algorithms, it is necessary an in-depth understanding of the hardness of the Travelling Salesman Problem instances. This requires to recognize which attributes allow a correct prediction of the hardness of the instances of Travelling Salesman Problem. In th

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P. E. Tanguay,R. Asarnow,R. Strandbergel proportion for each bag is known. The objective is to learn a model to predict the class labels of individual instances. This paradigm presents very different applications, specially concerning anonymous data. Two different iterative strategies are proposed to deal with this type of problems, bot

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Brain and Behavior in Child Psychiatrydescriptors associated with each object. However, general-purpose statistical packages offer a limited number of methods to perform such a comparison, and specific tools are required for each concrete problem. Weka is a freely-available framework that supports both supervised and unsupervised machin