Trainable superpixel segmentation
, 2018 Trainable Superpixel Segmentation is a plug-in developed for the ImageJ platform that aims at providing its users with the ability to train models to segment images by classifying superpixels using region-based image features. This project provides an underlying library that can be used independently, a graphic interface for ease of use and an ...
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A Graph-Based Superpixel Segmentation Approach Applied to Pansharpening. [PDF]
Sensors (Basel)Hallabia H.
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Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing. [PDF]
Sensors (Basel), 2017 Liu J, Tang Z, Cui Y, Wu G.
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Sagittal balance parameters measurement on cervical spine MR images based on superpixel segmentation. [PDF]
Front Bioeng BiotechnolZhong YF +24 more
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Multi-class semantic segmentation of oral cancer tissues on whole-slide images: A SuperPixel enhanced deep learning approach. [PDF]
J Pathol InformLeón F +6 more
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Vision-Based Automated Inspection of Box Meals for Food Portion Defects and Foreign Object Detection. [PDF]
Sensors (Basel)Lin HD, Chen GM, Lin CH.
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SLIC-Former: a superpixel-guided transformer framework for automatic liver segmentation in CT images. [PDF]
Sci RepElqersh SF +3 more
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Automatic Segmentation and Recognition of the Microstructure of High-Strength Low-Alloy Steel. [PDF]
Materials (Basel)Wang L +7 more
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Superpixel Random Selection Random Walk Multi-Branch Depthwise Convolutional Neural Network for Hyperspectral Image Classification. [PDF]
Sensors (Basel)Zhang K, Jiang X, Cai Z.
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