[PDF] Top 20 Attention Based Convolutional Neural Network for Machine Comprehension
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Attention Based Convolutional Neural Network for Machine Comprehension
... CNN based neural network system for open-domain machine comprehension ...by attention scheme from sentence level to snippet level, shows promising results in this ... See full document
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Performance evaluation of Convolutional Neural Network in classification of EEG signals based on attention task
... image classification recently. CNN has been used in various machine learning applications such as ImageNet [5]-[7], image segmentation [8], object detection [7], [9] and face recognition [10]-[12]. CNN had been ... See full document
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Color and Texture based Feature Extraction for Classifying Skin Cancer using Support Vector Machine and Convolutional Neural Network
... Farzam and Saied in 2017, is proposed an approach for melanoma skin cancer detection using color and texture features. They have introduced new texture features in their proposed work; they are Variance Mean Square ... See full document
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Patient Risk Assessment and Warning Symptom Detection Using Deep Attention Based Neural Networks
... an attention-based convolutional neu- ral network architecture trained on 600,000 doctor notes in ...is based on the learning of attention scores and a method of automatic ... See full document
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Neural Network-based Models with Commonsense Knowledge for Machine Reading Comprehension
... A scalable approach for commonsence ques- tion generation and a new dataset, which con- sists from more than 12000 multiple-choice ques- tions, was recently introduced by Talmor et al. (2019). In this dataset, questions ... See full document
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A Detection algorithm based on Convolutional Neural Network
... In the research of identification of the station logo, the theory mainly focuses on the following aspects: Firstly, the station logo detection based on the database template knowledge base and the statistical ... See full document
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Consensus Attention based Neural Networks for Chinese Reading Comprehension
... the attention result to directly pick the answer from the document, rather than computing the weighted sum representation of document using attention weights like the previous ...Pointer Network ... See full document
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Attention over Attention Neural Networks for Reading Comprehension
... baseline neural network model, as we did not observe a significant variance when changing the N-best list ...word- based setting and Kneser-Ney smoothing ... See full document
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Vehicle Recognition Based On Convolutional Neural Network
... Convolutional neural network (CNN) is a machine learning model for a deep supervised ...deep convolutional neural network image recognition andwon the first prize at a ... See full document
6
High Resolution Range Profile Sequence Recognition Based on ARTRBM
... stochastic neural network model named Attention based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed for the poor performance of the traditional HRRP recognition ... See full document
8
Co-Attention Based Neural Network for Source-Dependent Essay Scoring
... Mart´ın Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Cor- rado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael ... See full document
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Relation path feature embedding based convolutional neural network method for drug discovery
... ding based CNN with attention mechanism for discover- ing potential drugs from ...CNN based on attention mechanism can better identify the important relation feature of drug- disease, so that ... See full document
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Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network
... vector machine (SVM) and random forest (RF)] and three data-level methods [18, 19, 22] [the synthetic minority oversampling technique (SMOTE), borderline-SMOTE (BSMOTE) and under-sampling (UNDER)] for ... See full document
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Attention Based Convolutional Neural Network for Semantic Relation Extraction
... Nowadays, neural networks play an important role in the task of relation ...novel attention-based convolutional neural network architecture for this ...level attention ... See full document
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Attention based Recurrent Convolutional Neural Network for Automatic Essay Scoring
... Recently, Alikaniotis et al. (2016) employ a long short-term memory model to learn features for essay scoring task automatically without any predefined feature templates. It leverages score- specific word embeddings ... See full document
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ABCNN: Attention Based Convolutional Neural Network for Modeling Sentence Pairs
... incorporating attention into representations of local phrases detected by filters; in contrast, LSTMs encode the whole context to form attention-based word representations – a strategy that is more ... See full document
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DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY USING ADAPTIVE BOOSTING AND ARTIFICIAL NEURAL NETWORK
... Perception based binarisation was implemented to overcome the discontinuous lines in ...classification based on area and perimeter of blood vessels and hemorrhages produced significant results ... See full document
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CKY based Convolutional Attention for Neural Machine Translation
... new attention mechanism for neural machine transla- tion (NMT) based on convolutional neu- ral networks (CNNs), which is inspired by the CKY ...proposed attention, de- codes a ... See full document
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A Deep Learning Based Approach to Transliteration
... ral network based deep learning architec- tures for the transliteration of named en- ...different neural machine translation (NMT) frameworks: recurrent neural net- work and ... See full document
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A HYBRID MODEL FOR CLASSIFYING PLANT STRESSES
... is based on algorithms for learning multiple levels of representation to model complex relationships among ...present, Convolutional Neural Network (CNN) is the most common algorithm for deep ... See full document
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