Squeeze-and-Excitation Networks
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- Type
- preprint
- Published
- 2017-09-05
- Cited by
- 36,146
- References
- 85
- Access
- Open access
- OpenAlex
- https://openalex.org/W2752782242
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:140309863
Keywords
Computer science, Convolution (computer science), Block (permutation group theory), Convolutional neural network, Code (set theory)
References
- An Empirical Exploration of Recurrent Network Architectures
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- Training Very Deep Networks
- Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
- Multi-Level Discriminative Dictionary Learning With Application to Large Scale Image Classification
- Designing Neural Networks using Genetic Algorithms
- Rectified Linear Units Improve Restricted Boltzmann Machines
- Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Fully convolutional networks for semantic segmentation
- Image Classification with the Fisher Vector: Theory and Practice
- Speeding up Convolutional Neural Networks with Low Rank Expansions
- Long Short-Term Memory
- Linear spatial pyramid matching using sparse coding for image classification
- Going deeper with convolutions
- Evolving Neural Networks through Augmenting Topologies
- DeepPose: Human Pose Estimation via Deep Neural Networks
- A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information
- ImageNet Large Scale Visual Recognition Challenge
- A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
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- Deep learning and medical imaging.
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- A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion
- Learnable pooling with Context Gating for video classification
- Smart Health
- Learning Transferable Architectures for Scalable Image Recognition
- Normalized Direction-preserving Adam
- FiLM: Visual Reasoning with a General Conditioning Layer
- Learning Graph Convolution Filters from Data Manifold
- Not Merely Memorization in Deep Networks: Universal Fitting and Specific Generalization
- An Analysis of Scale Invariance in Object Detection - SNIP
- Light-Head R-CNN: In Defense of Two-Stage Object Detector
- Cascaded Pyramid Network for Multi-person Pose Estimation
- AOGNets: Deep AND-OR Grammar Networks for Visual Recognition
- Block-Cyclic Stochastic Coordinate Descent for Deep Neural Networks
- Deep Expander Networks: Efficient Deep Networks from Graph Theory
- Learning Channel Inter-dependencies at Multiple Scales on Dense Networks for Face Recognition
- 3DContextNet: K-d Tree Guided Hierarchical Learning of Point Clouds Using Local Contextual Cues
- Broadcasting Convolutional Network
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