Junmin Lyu

Reconstructing 3D voxels from ultra-sparse-view 2D X-ray images using a dual-domain balanced network

Ultra-sparse cone-beam computed tomography (CBCT) reconstruction is important for low-dose and rapid 3D imaging, including C-arm-assisted interventions, yet the Feldkamp-Davis-Kress (FDK) algorithm and simultaneous iterative reconstruction technique (SIRT) degrade under sparse views. We propose a cross-domain framewo...

H-FANet: A Hierarchical Multi-Scale Attention Network for Hyperspectral-LiDAR Land Cover Classification

H-FANet, a hierarchical fusion attention network with a three-branch backbone, improved land cover identification accuracy and could be applied to fields such as environmental monitoring, urban land use analysis, and ecological protection.

Artificial intelligence-driven energy storage optimization of renewable energy systems: From standalone to multi-energy systems

Dual-View X-ray to 3D CT Reconstruction via Discrete Latent Translation with VQ-VAE and Transformer

The proposed dual-view X-ray-to-CT reconstruction framework based on vector quantized variational autoencoders (VQ-VAEs) and Transformer-based latent code translation successfully synthesizes structurally plausible 3D CT volumes from only two X-ray views, and improves structural similarity and reduces reconstruction er...