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Methods/SpatialDropout

SpatialDropout

GeneralIntroduced 200028 papers

Description

SpatialDropout is a type of dropout for convolutional networks. For a given convolution feature tensor of size $n\_{\text{feats}}$ ×height×width, we perform only $n\_{\text{feats}}$ dropout trials and extend the dropout value across the entire feature map. Therefore, adjacent pixels in the dropped-out feature map are either all 0 (dropped-out) or all active as illustrated in the figure to the right.

Papers Using This Method

Early Explorations of Lightweight Models for Wound Segmentation on Mobile Devices2024-07-10 DocReal: Robust Document Dewarping of Real-Life Images via Attention-Enhanced Control Point Prediction2023-12-01 Resource Constrained Semantic Segmentation for Waste Sorting2023-10-30 Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml2022-05-16 Efficient Accelerator for Dilated and Transposed Convolution with Decomposition2022-05-02 Improving evidential deep learning via multi-task learning2021-12-17 Deep Learning Based Cardiac MRI Segmentation: Do We Need Experts?2021-07-23 AutoDropout: Learning Dropout Patterns to Regularize Deep Networks2021-01-05 MyFood: A Food Segmentation and Classification System to Aid Nutritional Monitoring2020-12-05 SelectScale: Mining More Patterns from Images via Selective and Soft Dropout2020-11-30 Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training2020-10-21 Reinforced Wasserstein Training for Severity-Aware Semantic Segmentation in Autonomous Driving2020-08-11 Deep Learning-based Aerial Image Segmentation with Open Data for Disaster Impact Assessment2020-06-10 Comparison of UNet, ENet, and BoxENet for Segmentation of Mast Cells in Scans of Histological Slices2019-09-15 Don't ignore Dropout in Fully Convolutional Networks2019-08-24 Learning Lightweight Lane Detection CNNs by Self Attention Distillation2019-08-02 DENet: A Universal Network for Counting Crowd with Varying Densities and Scales2019-04-17 Real time backbone for semantic segmentation2019-03-16 DSNet for Real-Time Driving Scene Semantic Segmentation2018-12-06 Efficient Semantic Segmentation for Visual Bird's-eye View Interpretation2018-11-29