Titlebook: Neural Information Processing; 24th International C Derong Liu,Shengli Xie,El-Sayed M. El-Alfy Conference proceedings 2017 Springer Interna

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Comparing Hybrid NN-HMM and RNN for Temporal Modeling in Gesture Recognitionand Recurrent Neural Networks (RNN) which have lately claimed the state-the-art performances. Experiments were conducted on both models in the same body of work, with similar representation learning capacity and comparable computational costs. For both solutions, we have integrated recent contributi

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Patterns Versus Characters in Subword-Aware Neural Language Modelingnd suffixes with which various nuances and relations to other words can be expressed. Thus, in order to build a proper word representation one must take into account its internal structure. From a corpus of texts we extract a set of frequent subwords and from the latter set we select patterns, i.e.

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Conference proceedings 2017 Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.?.

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Breast Cancer Malignancy Prediction Using Incremental Combination of Multiple Recurrent Neural Netwoes of clinical text including B-ultrasound, X-rays, Computed Tomography (CT), and Nuclear Magnetic Resonance Imaging (MRI), and then combines the generated features in an incremental way. Finally, we add one more recurrent neural network layer for classifying benign and malignant of breast cancer based on combined generated features.

擦試不掉

TinyPoseNet: A Fast and Compact Deep Network for Robust Head Pose Estimation so on. In addition, we introduce large angle data in Multi-PIE to verify the ability of dealing with large-scale pose in practice. All the experiments demonstrate the advantages of the proposed model.