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Under- and over-segmentation: New metrics for image segmentation accuracy measurement
Mobin Mohammadi +2 more
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Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation
ECCV Workshops, 2021In the past few years, convolutional neural networks (CNNs) have achieved milestones in medical image analysis. Especially, the deep neural networks based on U-shaped architecture and skip-connections have been widely applied in a variety of medical ...
Hu Cao +6 more
semanticscholar +1 more source
International Geoscience and Remote Sensing Symposium, 'Remote Sensing: Moving Toward the 21st Century'., 1989
Based on an SAR speckle statistical model, the authors investigate the feasibility of segmenting SAR images based on a gray-level histogram for one-look and multilook processed SAR images. The classification errors are evaluated and a procedure for the multilevel thresholding of SAR images is devised.
J.-S. Lee, I. Jurkevich
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Based on an SAR speckle statistical model, the authors investigate the feasibility of segmenting SAR images based on a gray-level histogram for one-look and multilook processed SAR images. The classification errors are evaluated and a procedure for the multilevel thresholding of SAR images is devised.
J.-S. Lee, I. Jurkevich
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IEEE Transactions on Biomedical Engineering, 1999
Characteristics of microscopic structures in bone cross sections carry essential clues in age determination in forensic science and in the study of age-related bone developments and bone diseases. Analysis of bone cross sections represents a major area of research in bone biology. However, traditional approaches in bone biology have relied primarily on
Z Q, Liu +3 more
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Characteristics of microscopic structures in bone cross sections carry essential clues in age determination in forensic science and in the study of age-related bone developments and bone diseases. Analysis of bone cross sections represents a major area of research in bone biology. However, traditional approaches in bone biology have relied primarily on
Z Q, Liu +3 more
openaire +2 more sources
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
semanticscholar +1 more source
Medical Transformer: Gated Axial-Attention for Medical Image Segmentation
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2021Over the past decade, Deep Convolutional Neural Networks have been widely adopted for medical image segmentation and shown to achieve adequate performance.
Jeya Maria Jose Valanarasu +3 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 1979
This correspondence describes research in the development of symbolic registration techniques directed toward the comparison of pairs of images of the same scene to ultimately generate descriptions of the changes in the scene. Unlike most earlier work in image registration, all the matching and analysis will be performed at a symbolic level rather than
K, Price, R, Reddy
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This correspondence describes research in the development of symbolic registration techniques directed toward the comparison of pairs of images of the same scene to ultimately generate descriptions of the changes in the scene. Unlike most earlier work in image registration, all the matching and analysis will be performed at a symbolic level rather than
K, Price, R, Reddy
openaire +2 more sources