Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks with Learned Shape Features

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There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an approach to volume ...

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This paper introduces TACOSS a text-image alignment approach that allows explainable land cover semantic segmentation by directly integrating semantic concepts encoded from texts. TACOSS combines convolutional neural networks for visual feature extraction ...

Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks with Learned Shape Features

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Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Multi-site, Multi-domain Airway Tree Modeling

Digital twins for post-earthquake damage assessment of free-standing buildings including damage information

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Correlated-photon imaging at 10 volumetric images per second

Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

Reshaping Perception for Autonomous Driving with Semantic Keypoints

Text as a Richer Source of Supervision in Semantic Segmentation Tasks