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A survey on deep learning and its applications
Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …
Image segmentation using deep learning: A survey
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …
applications such as scene understanding, medical image analysis, robotic perception …
2dpass: 2d priors assisted semantic segmentation on lidar point clouds
As camera and LiDAR sensors capture complementary information in autonomous driving,
great efforts have been made to conduct semantic segmentation through multi-modality data …
great efforts have been made to conduct semantic segmentation through multi-modality data …
Self-support few-shot semantic segmentation
Existing few-shot segmentation methods have achieved great progress based on the
support-query matching framework. But they still heavily suffer from the limited coverage of …
support-query matching framework. But they still heavily suffer from the limited coverage of …
Vitaev2: Vision transformer advanced by exploring inductive bias for image recognition and beyond
Vision transformers have shown great potential in various computer vision tasks owing to
their strong capability to model long-range dependency using the self-attention mechanism …
their strong capability to model long-range dependency using the self-attention mechanism …
Perturbed and strict mean teachers for semi-supervised semantic segmentation
Consistency learning using input image, feature, or network perturbations has shown
remarkable results in semi-supervised semantic segmentation, but this approach can be …
remarkable results in semi-supervised semantic segmentation, but this approach can be …
Vitae: Vision transformer advanced by exploring intrinsic inductive bias
Transformers have shown great potential in various computer vision tasks owing to their
strong capability in modeling long-range dependency using the self-attention mechanism …
strong capability in modeling long-range dependency using the self-attention mechanism …
Polarized self-attention: Towards high-quality pixel-wise regression
Pixel-wise regression is probably the most common problem in fine-grained computer vision
tasks, such as estimating keypoint heatmaps and segmentation masks. These regression …
tasks, such as estimating keypoint heatmaps and segmentation masks. These regression …
Strip pooling: Rethinking spatial pooling for scene parsing
Spatial pooling has been proven highly effective to capture long-range contextual
information for pixel-wise prediction tasks, such as scene parsing. In this paper, beyond …
information for pixel-wise prediction tasks, such as scene parsing. In this paper, beyond …
A brief survey on semantic segmentation with deep learning
Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …
performance of semantic segmentation has been greatly improved by using deep learning …