SenseAI: Real-Time Inpainting for Electron Microscopy
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 sin...
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| creator | Wells, Jack Moshtaghpour, Amirafshar Nicholls, Daniel Robinson, Alex W Zheng, Yalin Castagna, Jony Browning, Nigel D |
| description | 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. |
| doi_str_mv | 10.48550/arxiv.2311.15061 |
| format | Article |
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(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.</description><identifier>DOI: 10.48550/arxiv.2311.15061</identifier><language>eng</language><creationdate>2023-11</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2311.15061$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2311.15061$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Wells, Jack</creatorcontrib><creatorcontrib>Moshtaghpour, Amirafshar</creatorcontrib><creatorcontrib>Nicholls, Daniel</creatorcontrib><creatorcontrib>Robinson, Alex W</creatorcontrib><creatorcontrib>Zheng, Yalin</creatorcontrib><creatorcontrib>Castagna, Jony</creatorcontrib><creatorcontrib>Browning, Nigel D</creatorcontrib><title>SenseAI: Real-Time Inpainting for Electron Microscopy</title><description>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
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(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.</abstract><doi>10.48550/arxiv.2311.15061</doi><oa>free_for_read</oa></addata></record> |
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| title | SenseAI: Real-Time Inpainting for Electron Microscopy |
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