S3Pool: Pooling with Stochastic Spatial Sampling
Explore this paper's citation graph
- Type
- article
- Published
- 2016-11-16
- Cited by
- 87
- References
- 31
- Access
- Open access
- OpenAlex
- https://openalex.org/W2559156603
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:8431399
Keywords
Pooling, Upsampling, Computer science, Convolutional neural network, Feature (linguistics)
References
- ADADELTA: An Adaptive Learning Rate Method
- Deep Representation Learning with Target Coding
- Stacked What-Where Auto-encoders
- Sampling theory in Fourier and signal analysis : foundations
- Pyramid Match Kernels: Discriminative Classification with Sets of Image Features (version 2)
- Dropout: a simple way to prevent neural networks from overfitting
- The pyramid match kernel: discriminative classification with sets of image features
- Selecting Receptive Fields in Deep Networks
- Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
- Gradient-based learning applied to document recognition
- Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
- Fractional Max-Pooling
- Discriminative Unsupervised Feature Learning with Convolutional Neural Networks
- Best practices for convolutional neural networks applied to visual document analysis
- Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition
- Task-Driven Feature Pooling for Image Classification
- Deep Multi-patch Aggregation Network for Image Style, Aesthetics, and Quality Estimation
- Deconvolutional networks
Cited by
- A Survey of Model Compression and Acceleration for Deep Neural Networks
- Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges
- Parallel Grid Pooling for Data Augmentation
- Ordinal Pooling Networks: For Preserving Information over Shrinking Feature Maps
- Detail-Preserving Pooling in Deep Networks
- Improving the Resolution of CNN Feature Maps Efficiently with Multisampling
- Stacked Pooling: Improving Crowd Counting by Boosting Scale Invariance
- Learning Scale-Aware Optical Flow
- A Hybrid Approach with Optimization and Metric-based Meta-Learner for Few-Shot Learning
- Stochastic Region Pooling: Make Attention More Expressive
- Implicit Label Augmentation on Partially Annotated Clips via Temporally-Adaptive Features Learning
- Expectation pooling: an effective and interpretable pooling method for predicting DNA–protein binding
- Interpretation of intelligence in CNN-pooling processes: a methodological survey
- Mixed-Supervised Dual-Network for Medical Image Segmentation
- An object Detection System Based on YOLOv2 in Fashion Apparel
- Deep hash for latent image retrieval
- Salience Guided Pooling in Deep Convolutional Networks
- Gaussian-Based Pooling for Convolutional Neural Networks
- DCT Based Information-Preserving Pooling for Deep Neural Networks
- Global Feature Guided Local Pooling
Related papers
- Term-based pooling in convolutional neural networks for text classification
- Pooling and Convolution Layer Strategy on CNN for Melanoma Detection
- Good Practice in CNN Feature Transfer
- A Normalized Convolutional Neural Network for Guided Sparse Depth Upsampling
- Deep Neural Networks for Dynamic Visual Data
- Feature-level fusion of convolutional neural networks for visual object classification
- Pixel selection in a face image based on discriminant features for face recognition
- Pixel selection based on discriminant features with application to face recognition