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Tomographic Reconstructions
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Neural Vector Tomography for Reconstructing a Magnetization Vector Field
Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model
Physics-informed neural networks for diffraction tomography
WNet: A data-driven dual-domain denoising model for sparse-view computed tomography with a trainable reconstruction layer
SHREC 2021: Classification in cryo-electron tomograms
Accelerated iterative tomographic reconstruction with x-ray edge illumination
Disassemblable Fieldwork CT Scanner Using a 3D-printed Calibration Phantom
A Learning-based Method for Online Adjustment of C-arm Cone-Beam CT Source Trajectories for Artifact Avoidance
Full-pulse Tomographic Reconstruction with Deep Neural Networks
Model based learning for accelerated, limited-view 3D photoacoustic tomography
Adaptive Graph-based Total Variation for Tomographic Reconstructions
Improving analytical tomographic reconstructions through consistency conditions
Graph Based Sinogram Denoising for Tomographic Reconstructions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.