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Multi-modal semantic image segmentation
Computer Vision and Image Understanding, 2021Abstract We propose a modality invariant method to obtain high quality semantic object segmentation of human body parts, for four imaging modalities which consist of visible images, X-ray images, thermal images (heatmaps) and infrared radiation (IR) images. We first consider two modalities (i.e.
Pemasiri, Akila +3 more
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Semantic Segmentation of Radio-Astronomical Images
2021In the context of next-generation radio-astronomical visual surveys, automated object detection and segmentation are necessary tasks to support astrophysics research from observations. Indeed, identifying manually astronomical sources (e.g., galaxies) from the daunting amount of acquired images is largely unfeasible, greatly limiting the huge potential
Pino, Carmelo +4 more
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Deformable attention (DANet) for semantic image segmentation
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022Deep learning based medical image segmentation is currently a widely researched topic. Attention mechanism used with deep networks significantly benefit semantic segmen-tation tasks. The recent criss-cross-attention module captures global self-attention while remaining memory and time efficient.
Kumar, Rajamani +3 more
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Guided Filter Network for Semantic Image Segmentation
IEEE Transactions on Image Processing, 2022The existing publicly available datasets with pixel-level labels contain limited categories, and it is difficult to generalize to the real world containing thousands of categories. In this paper, we propose an approach to generate object masks with detailed pixel-level structures/boundaries automatically to enable semantic image segmentation of ...
Xiang Zhang +4 more
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Semantic segmentation of angiographic images
Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2002The overall purpose of this work is to identify objects in an angiographic sequence by exploiting the temporal correlation between adjacent frames for analysis and compression purposes. The detection of the vascular tree in a reference image can support segmentation in adjacent frames by reducing the detection problem to a tracking procedure along the ...
Menegaz, Gloria, Lancini, Rosa
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Semantic Image Segmentation by Scale-Adaptive Networks
IEEE Transactions on Image Processing, 2020Semantic image segmentation is an important yet unsolved problem. One of the major challenges is the large variability of the object scales. To tackle this scale problem, we propose a Scale-Adaptive Network (SAN) which consists of multiple branches with each one taking charge of the segmentation of the objects of a certain range of scales.
Zilong Huang +4 more
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Semantic Segmentation For Aerial Images
International Journal of Research Publication and ReviewsSemantic segmentation of aerial imagery plays a critical role in modern urban planning, environmental monitoring, and the development of smart cities. This project presents an interactive webbased application that performs semantic segmentation on high-resolution aerial images using a deep learning-based U-Net model.
Dr. B. Harika, M. Bharath, K. Himneesh
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