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Tomography
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SaSi: A Self-augmented and Self-interpreted Deep Learning Approach for Few-shot Cryo-ET Particle Detection
2.5D U-Net with Depth Reduction for 3D CryoET Object Identification
Online Learning of Pure States is as Hard as Mixed States
Revisiting $Ψ$DONet: microlocally inspired filters for incomplete-data tomographic reconstructions
End-to-end localized deep learning for Cryo-ET
Fast and Provable Tensor-Train Format Tensor Completion via Precondtioned Riemannian Gradient Descent
Neural Vector Tomography for Reconstructing a Magnetization Vector Field
J-Invariant Volume Shuffle for Self-Supervised Cryo-Electron Tomogram Denoising on Single Noisy Volume
A novel algorithm for optimizing bundle adjustment in image sequence alignment
CryoFM: A Flow-based Foundation Model for Cryo-EM Densities
Near-Isotropic Sub-Ångstrom 3D Resolution Phase Contrast Imaging Achieved by End-to-End Ptychographic Electron Tomography
Training-free CryoET Tomogram Segmentation
Universal Quantum Tomography With Deep Neural Networks
Frontiers in integrative structural biology: modeling disordered proteins and utilizing in situ data
Learning pure quantum states (almost) without regret
Vox-UDA: Voxel-wise Unsupervised Domain Adaptation for Cryo-Electron Subtomogram Segmentation with Denoised Pseudo Labeling
Comprehensive characterization of three-qubit Grover search algorithm on IBM's 127-qubit superconducting quantum computers
Disruption of the mitochondrial network in a mouse model of Huntington's disease visualized by in tissue multiscale 3D electron microscopy
Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks
Tracing and segmentation of molecular patterns in 3-dimensional cryo-et/em density maps through algorithmic image processing and deep learning-based techniques
Ice-Tide: Implicit Cryo-ET Imaging and Deformation Estimation
A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomography
Online Learning Quantum States with the Logarithmic Loss via VB-FTRL
Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging
Learning quantum states and unitaries of bounded gate complexity
Learning Informative Latent Representation for Quantum State Tomography
Imaging structurally dynamic ribosomes with cryogenic electron microscopy
ShadowNet for Data-Centric Quantum System Learning
Quantum State Tomography using Quantum Machine Learning
Implicit Reconstructions from Deformed Projections for CryoET
MORE: Measurement and Correlation Based Variational Quantum Circuit for Multi-classification
Tomography of Quantum States from Structured Measurements via quantum-aware transformer
Real-Time Tilt Undersampling Optimization during Electron Tomography of Beam Sensitive Samples using Golden Ratio Scanning and RECAST3D
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model
Unrolling SVT to obtain computationally efficient SVT for n-qubit quantum state tomography
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