Titlebook: Engineering Applications of Neural Networks; 18th International C Giacomo Boracchi,Lazaros Iliadis,Aristidis Likas Conference proceedings 2

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Boosted Residual Networksnetwork at each round of boosting. The proposed approach combines recent developements in Residual Networks?- a method for creating very deep networks by including a shortcut layer between different groups of layers - with the Deep Incremental Boosting, which has been proposed as a methodology to tr

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A Convolutional Approach to Multiword Expression Detection Based on Unsupervised Distributed Word Rere for a specific task - multiword expression detection - and we compare our results to state-of-the-art systems on the same datasets. The approach is multilingual and we rely on automatically extracted word embeddings from Wikipedia dumps. We also show that task-driven lexical features embeddings i

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Remarks on Tea Leaves Aroma Recognition Using Deep Neural Networkaves using an array of quartz crystal resonators coated with plasma organic polymer films. Frequency analysis based on continuous wavelet transform, with the Morlet function as the mother wavelet, was applied to the sensor signals to construct the input vectors of the deep neural network. Experiment

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Baby Cry Sound Detection: A Comparison of Hand Crafted Features and Deep Learning Approachserver architecture where an end-node device streams the audio to a centralized server in charge of the detection. Even providing the best performances, these solutions raise power consumption and privacy issues. For these reasons, interest has recently grown in the community for methods which can r

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Communications in Computer and Information Sciencehttp://image.papertrans.cn/e/image/310712.jpg

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978-3-319-65171-2Springer International Publishing AG 2017

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Engineering Applications of Neural Networks978-3-319-65172-9Series ISSN 1865-0929 Series E-ISSN 1865-0937

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Decheng Zhao,Bo Yan,Liwei Tang,Yao Zhouer stress accurately, no method has been practically applied yet due to the high cost of equipment. Thus, the previous methods have a trade-off relationship between cost and estimation accuracy. In this paper, we propose a method for estimating water stress on the basis of plant images and sensor da