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Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
BrainLes@MICCAI, 2022Semantic segmentation of brain tumors is a fundamental medical image analysis task involving multiple MRI imaging modalities that can assist clinicians in diagnosing the patient and successively studying the progression of the malignant entity. In recent
Ali Hatamizadeh +5 more
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Rich feature hierarchies for accurate object detection and semantic segmentation
Radioengineering, 2021Formulation of the problem. Over the past few years, there has been little progress in object detection techniques. The most efficient are complex computational ensemble methods, which usually combine several low-level image properties with high-level ...
A.Y. Virasova +4 more
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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
European Conference on Computer Vision, 2018Spatial pyramid pooling module or encode-decoder structure are used in deep neural networks for semantic segmentation task. The former networks are able to encode multi-scale contextual information by probing the incoming features with filters or pooling
Liang-Chieh Chen +4 more
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BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation
International Journal of Computer Vision, 2020Low-level details and high-level semantics are both essential to the semantic segmentation task. However, to speed up the model inference, current approaches almost always sacrifice the low-level details, leading to a considerable decrease in accuracy ...
Changqian Yu +5 more
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Object-Contextual Representations for Semantic Segmentation
European Conference on Computer Vision, 2019In this paper, we address the semantic segmentation problem with a focus on the context aggregation strategy. Our motivation is that the label of a pixel is the category of the object that the pixel belongs to. We present a simple yet effective approach,
Yuhui Yuan, Xilin Chen, Jingdong Wang
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ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation
Computer Vision and Pattern Recognition, 2018Semantic segmentation is a key problem for many computer vision tasks. While approaches based on convolutional neural networks constantly break new records on different benchmarks, generalizing well to diverse testing environments remains a major ...
Tuan-Hung Vu +4 more
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ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation
IEEE transactions on intelligent transportation systems (Print), 2018Eduardo Romera +3 more
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