Description
ENet Dilated Bottleneck is an image model block used in the ENet semantic segmentation architecture. It is the same as a regular ENet Bottleneck but employs dilated convolutions instead.
Papers Using This Method
Early Explorations of Lightweight Models for Wound Segmentation on Mobile Devices2024-07-10DocReal: Robust Document Dewarping of Real-Life Images via Attention-Enhanced Control Point Prediction2023-12-01Resource Constrained Semantic Segmentation for Waste Sorting2023-10-30Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml2022-05-16Efficient Accelerator for Dilated and Transposed Convolution with Decomposition2022-05-02Improving evidential deep learning via multi-task learning2021-12-17Deep Learning Based Cardiac MRI Segmentation: Do We Need Experts?2021-07-23MyFood: A Food Segmentation and Classification System to Aid Nutritional Monitoring2020-12-05Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training2020-10-21Reinforced Wasserstein Training for Severity-Aware Semantic Segmentation in Autonomous Driving2020-08-11Deep Learning-based Aerial Image Segmentation with Open Data for Disaster Impact Assessment2020-06-10Comparison of UNet, ENet, and BoxENet for Segmentation of Mast Cells in Scans of Histological Slices2019-09-15Learning Lightweight Lane Detection CNNs by Self Attention Distillation2019-08-02DENet: A Universal Network for Counting Crowd with Varying Densities and Scales2019-04-17Real time backbone for semantic segmentation2019-03-16DSNet for Real-Time Driving Scene Semantic Segmentation2018-12-06Efficient Semantic Segmentation for Visual Bird's-eye View Interpretation2018-11-29SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle properties2018-10-09A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation2018-07-16Mapping Road Lanes Using Laser Remission and Deep Neural Networks2018-04-27