Deepmulticut: Deep learning of multicut problem for neuron segmentation from electron microscopy volume
Superpixel aggregation is a powerful tool for automated neuron segmentation from electron
microscopy (EM) volume. However, existing graph partitioning methods for superpixel …
microscopy (EM) volume. However, existing graph partitioning methods for superpixel …
A data-driven approach for volume feature recognition based on cell graph
D Yang, Y Li, X Liu, T Deng, C Liu… - International Journal of …, 2024 - Taylor & Francis
Machining feature recognition is one of the key technologies for realizing automated process
planning. The machining feature represented by volume contains more complete …
planning. The machining feature represented by volume contains more complete …
I Spy With My Little Eye: A Minimum Cost Multicut Investigation of Dataset Frames
Visual framing analysis is a key method in social sciences for determining common themes
and concepts in a given discourse. To reduce manual effort, image clustering can …
and concepts in a given discourse. To reduce manual effort, image clustering can …
Learning to solve minimum cost multicuts efficiently using edge-weighted graph convolutional neural networks
The minimum cost multicut problem is the NP-hard/APX-hard combinatorial optimization
problem of partitioning a real-valued edge-weighted graph such as to minimize the total cost …
problem of partitioning a real-valued edge-weighted graph such as to minimize the total cost …
[HTML][HTML] Minimum cost multicuts for image and motion segmentation
A Kardoost - 2023 - 141.99.19.133
Clustering and its application in computer vision, such as image, mesh data, video, and
motion segmentation, are the main topics we discuss in this dissertation. The clustering of …
motion segmentation, are the main topics we discuss in this dissertation. The clustering of …