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MCTGCL: Mixed CNN–Transformer for Mars Hyperspectral Image Classification With Graph Contrastive Learning

IEEE Transactions on Geoscience and Remote Sensing
Hyperspectral image (HSI) classification has been extensively studied in the context of Earth observation. However, its application in Mars exploration remains limited. Although convolutional neural networks (CNNs) have proven effective in HSI processing,
Bobo Xi   +8 more
semanticscholar   +1 more source

MMGDreamer: Mixed-Modality Graph for Geometry-Controllable 3D Indoor Scene Generation

AAAI Conference on Artificial Intelligence
Controllable 3D scene generation has extensive applications in virtual reality and interior design, where the generated scenes should exhibit high levels of realism and controllability in terms of geometry.
Zhifei Yang   +12 more
semanticscholar   +1 more source

Relation between the Hermitian energy of a mixed graph and the matching number of its underlying graph

Linear and multilinear algebra, 2018
Given a graph G, the mixed graph is obtained from G by orienting some of its edges (G is also called the underlying graph of ). Let be the Hermitian energy of and let be the matching number of the underlying graph G. In this paper, we first establish the
Wei Wei, Shuchao Li
semanticscholar   +1 more source

Universal Symmetry Constraint Extraction for Analog and Mixed-Signal Circuits with Graph Neural Networks

Design Automation Conference, 2021
Recent research trends in analog layout synthesis aim for a fully automated netlist-to-GDSII design flow with minimum human efforts. Due to the sensitiveness of analog circuit layouts, symmetry matching between critical building blocks and devices can ...
Hao Chen   +5 more
semanticscholar   +1 more source

Mixed Roman Domination in Graphs

Bulletin of the Malaysian Mathematical Sciences Society, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ahangar, H. Abdollahzadeh   +2 more
openaire   +3 more sources

ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph

IEEE International Conference on Computer Vision, 2015
This work focuses on the problem of multi-label learning with missing labels (MLML), which aims to label each test instance with multiple class labels given training instances that have an incomplete/partial set of these labels (i.e. some of their labels
Baoyuan Wu, Siwei Lyu, Bernard Ghanem
semanticscholar   +1 more source

Mixed Graph Problems

1994
All of the situations considered earlier can be interpreted in terms of resource-constrained project scheduling. To do so, we introduce the concept of an Operation as some process having a certain duration and consuming certain resources. Each two operations may be either dependent or independent in the sense that the calendar time of one of them ...
V. S. Tanaev   +2 more
openaire   +1 more source

Multi-View Graph Convolution Network Reinforcement Learning for CAVs Cooperative Control in Highway Mixed Traffic

IEEE Transactions on Intelligent Vehicles
The control of connected autonomous vehicles (CAVs) for cooperative sensing and driving in mixed traffic flows is critical for the development of intelligent transportation systems.
Dongwei Xu   +5 more
semanticscholar   +1 more source

On mixed block graphs

Linear and Multilinear Algebra, 2017
A mixed complete graph is obtained from a directed cycle of length at least three by adding all the possible arcs between any non-adjacent vertices of the underlying cycle. A mixed block graph is a strongly connected directed graph whose blocks are mixed complete graphs. In this paper, we give the inverse of the distance matrix of the mixed block graph.
Hui Zhou, Qi Ding
openaire   +1 more source

Mixed matchings in graphs

Discrete Mathematics, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

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