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Superdense-scale network for semantic segmentation

https://doi.org/10.1016/j.neucom.2022.06.103
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01234-2_49openalex-snapshot
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-030-58548-8_7openalex-snapshot
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1007/s11263-009-0275-4openalex-snapshot
The Pascal Visual Object Classes (VOC) Challenge
inferredcites →https://doi.org/10.1007/s11263-015-0816-yopenalex-snapshot
ImageNet Large Scale Visual Recognition Challenge
inferredcites →https://doi.org/10.1016/j.isprsjprs.2017.12.007openalex-snapshot
Semantic labeling in very high resolution images via a self-cascaded convolutional neural network
inferredcites →https://doi.org/10.1016/j.neucom.2020.05.082openalex-snapshot
Discriminant sub-dictionary learning with adaptive multiscale superpixel representation for hyperspectral image classification
inferredcites →https://doi.org/10.1016/j.neucom.2021.04.002openalex-snapshot
Adaptive multiscale feature for object detection
inferredcites →https://doi.org/10.1016/j.neucom.2021.04.106openalex-snapshot
Self-attention feature fusion network for semantic segmentation
inferredcites →https://doi.org/10.1016/j.neucom.2021.06.068openalex-snapshot
Adaptive multi-scale dual attention network for semantic segmentation
inferredcites →https://doi.org/10.1016/j.neucom.2021.08.009openalex-snapshot
RGB × D: Learning depth-weighted RGB patches for RGB-D indoor semantic segmentation
inferredcites →https://doi.org/10.1016/j.neucom.2021.08.031openalex-snapshot
A joint object detection and semantic segmentation model with cross-attention and inner-attention mechanisms
inferredcites →https://doi.org/10.1109/cvpr.1993openalex-snapshot
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.549openalex-snapshot
RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2019.00064openalex-snapshot
Co-Occurrent Features in Semantic Segmentation
inferredcites →https://doi.org/10.1109/iccv.1995.466933openalex-snapshot
Proceedings of IEEE International Conference on Computer Vision
inferredcites →https://doi.org/10.1109/tgrs.2019.2899955openalex-snapshot
$\mathcal{R}^2$ -CNN: Fast Tiny Object Detection in Large-Scale Remote Sensing Images
inferredcites →https://doi.org/10.1109/tii.2018.2849348openalex-snapshot
Fast Semantic Segmentation for Scene Perception
inferredcites →https://doi.org/10.1109/tpami.2017.2699184openalex-snapshot
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
inferredcites →https://doi.org/10.1109/tpami.2020.2983686openalex-snapshot
Deep High-Resolution Representation Learning for Visual Recognition
inferredcites →https://doi.org/10.1109/wacv.2018.00163openalex-snapshot
Understanding Convolution for Semantic Segmentation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4528608openalex-extracted
Real-Time Semantic Segmentation Via Mutual Optimization of Spatial Details and Semantic Information
inferred← citeshttps://doi.org/10.1007/s10489-023-04935-4openalex-snapshot
Dense-scale dynamic network with filter-varying atrous convolution for semantic segmentation
inferred← citeshttps://doi.org/10.1007/s40747-024-01582-1openalex-snapshot
HRDLNet: a semantic segmentation network with high resolution representation for urban street view images
inferred← citeshttps://doi.org/10.1016/j.displa.2025.103225openalex-snapshot
Review of deep learning-based segmentation methods: Popular approaches, literature gaps, and opportunities
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122695openalex-snapshot
Scale-pyramid dynamic atrous convolution for pixel-level labeling
inferred← citeshttps://doi.org/10.1016/j.jag.2022.103062openalex-snapshot
Dense context distillation network for semantic parsing of oblique UAV images
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.129982openalex-snapshot
GCD-Net: Global consciousness-driven open-vocabulary semantic segmentation network
inferred← citeshttps://doi.org/10.3233/jifs-235929openalex-snapshot
RETRACTED: Real-time semantic segmentation via mutual optimization of spatial details and semantic information
inferred← citeshttps://doi.org/10.3390/app13148512openalex-snapshot
An Improved Multi-Scale Feature Fusion for Skin Lesion Segmentation
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