Convolutional recurrent neural networks: Learning spatial dependencies for image representation
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- Type
- article
- Published
- 2015-06-07
- Cited by
- 170
- References
- 56
- OpenAlex
- https://openalex.org/W1922658220
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:16889475
Keywords
Computer science, Artificial intelligence, Recurrent neural network, Discriminative model, Pattern recognition (psychology)
References
- Recurrent neural network based language model
- Recurrent Convolutional Neural Networks for Scene Labeling
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Image Classification with the Fisher Vector: Theory and Practice
- Return of the Devil in the Details: Delving Deep into Convolutional Nets
- Deep Learning Face Representation from Predicting 10,000 Classes
- SUN database: Large-scale scene recognition from abbey to zoo
- Blocks That Shout: Distinctive Parts for Scene Classification
- Joint Feature Learning for Face Recognition
- Video Tracking Using Learned Hierarchical Features
- Learning Important Spatial Pooling Regions for Scene Classification
- Scalable Multitask Representation Learning for Scene Classification
- Going deeper with convolutions
- Max-Margin Multiple-Instance Dictionary Learning
- Towards End-To-End Speech Recognition with Recurrent Neural Networks
- Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
- Harvesting Mid-level Visual Concepts from Large-Scale Internet Images
- ImageNet: A large-scale hierarchical image database
- Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
- Finding Structure in Time
Cited by
- Quaddirectional 2D-Recurrent Neural Networks For Image Labeling
- Exemplar based Deep Discriminative and Shareable Feature Learning for scene image classification
- An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition
- Dense Recurrent Neural Networks for Scene Labeling
- Learning Contextual Dependence With Convolutional Hierarchical Recurrent Neural Networks
- Locally Supervised Deep Hybrid Model for Scene Recognition
- Human detection and tracking in surveillance videos
- Improved Representation Learning for Question Answer Matching
- Riemannian Manifold-Based Modeling and Classification Methods for Video Activities with Applications to Assisted Living and Smart Home
- Sentiment classification using Comprehensive Attention Recurrent models
- Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis
- Convolutional Recurrent Neural Networks forHyperspectral Data Classification
- Deep Contextual Recurrent Residual Networks for Scene Labeling
- Spatial–Temporal Recurrent Neural Network for Emotion Recognition
- Leveraging Structural Context Models and Ranking Score Fusion for Human Interaction Prediction
- Scene Segmentation with DAG-Recurrent Neural Networks
- Online object tracking based on BLSTM-RNN with contextual-sequential labeling
- Teaching Development Project: Gene Expression Prediction With Deep Learning
- MCCT: a multi-channel complementary census transform for image classification
- Multimodal Recurrent Neural Networks With Information Transfer Layers for Indoor Scene Labeling
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