SenseAI: Real-Time Inpainting for Electron Microscopy
원문 초록
Despite their proven success and broad applicability to Electron Microscopy (EM) data, joint dictionary-learning and sparse-coding based inpainting algorithms have so far remained impractical for real-time usage with an Electron Microscope. For many EM applications, the reconstruction time for a single frame is orders of magnitude longer than the data acquisition time, making it impossible to perform exclusively subsampled acquisition. This limitation has led to the development of SenseAI, a C++/CUDA library capable of extremely efficient dictionary-based inpainting. SenseAI provides N-dimensional dictionary learning, live reconstructions, dictionary transfer and visualization, as well as real-time plotting of statistics, parameters, and image quality metrics.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Decomposing MLP Activations into Interpretable Features via Semi-Nonnegative Matrix Factorization
Interpreting Large Text-to-Image Diffusion Models with Dictionary Learning
DB-KSVD: Scalable Alternating Optimization for Disentangling High-Dimensional Embedding Spaces
Modeling Musical Genre Trajectories through Pathlet Learning
Towards Understanding the Nature of Attention with Low-Rank Sparse Decomposition
Topological Dictionary Learning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.