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Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths
TLDR
This paper presents SDP-LSTM, a novel neural network to classify the relation of two entities in a sentence, which leverages the shortest dependency path (SDP) between two entities; multichannel recurrent neural networks, with long short term memory (L STM) units, pick up heterogeneous information along the SDP. Expand
Convolutional Neural Networks over Tree Structures for Programming Language Processing
TLDR
A novel tree-based convolutional neural network (TBCNN) is proposed for programming language processing, in which a convolution kernel is designed over programs' abstract syntax trees to capture structural information. Expand
Deep Code Comment Generation
TLDR
DeepCom applies Natural Language Processing (NLP) techniques to learn from a large code corpus and generates comments from learned features for better comments generation of Java methods. Expand
Natural Language Inference by Tree-Based Convolution and Heuristic Matching
TLDR
This model, a tree-based convolutional neural network (TBCNN) captures sentence-level semantics; then heuristic matching layers like concatenation, element-wise product/difference combine the information in individual sentences. Expand
How Transferable are Neural Networks in NLP Applications?
TLDR
In this paper, systematic case studies are conducted and an illuminating picture is provided on the transferability of neural networks in NLP. Expand
Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation
TLDR
This paper proposes seq2BF, a “sequence to backward and forward sequences” model, which generates a reply containing the given keyword, and significantly outperforms traditional sequence-to-sequence models in terms of human evaluation and the entropy measure. Expand
A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement
TLDR
A dual-exposure fusion algorithm is proposed to provide an accurate contrast and lightness enhancement to solve the problem of low-light image enhancement through image fusion and weight matrix fusion. Expand
StructureFlow: Image Inpainting via Structure-Aware Appearance Flow
TLDR
A two-stage model which splits the inpainting task into two parts: structure reconstruction and texture generation is proposed, which shows superior performance on multiple publicly available datasets. Expand
Graph Convolutional Label Noise Cleaner: Train a Plug-And-Play Action Classifier for Anomaly Detection
TLDR
A graph convolutional network is devised that propagates supervisory signals from high-confidence snippets to low-confidence ones and is capable of providing cleaned supervision for action classifiers. Expand
An Innovative Salient Object Detection Using Center-Dark Channel Prior
TLDR
The proposed algorithm is evaluated on two public RGB-D datasets, and the experimental results show that the method outperforms the state-of-the-art methods. Expand
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