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A knowledge-integrated deep learning framework for cellular image analysis in parasite microbiology
Cellular image analysis is an important method for microbiologists to identify and study microbes. Here, we present a knowledge-integrated deep learning framework for cellular image analysis, using three tasks as examples: classification, detection, and reconstruction. Alongside thorough description...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10410587/ https://www.ncbi.nlm.nih.gov/pubmed/37537845 http://dx.doi.org/10.1016/j.xpro.2023.102452 |
Sumario: | Cellular image analysis is an important method for microbiologists to identify and study microbes. Here, we present a knowledge-integrated deep learning framework for cellular image analysis, using three tasks as examples: classification, detection, and reconstruction. Alongside thorough descriptions of different models and datasets, we describe steps for computing environment setup, knowledge representation, data pre-processing, and training and tuning. We then detail evaluation and visualization. For complete details on the use and execution of this protocol, please refer to Li et al. (2021),(1) Jiang et al. (2020),(2) and Zhang et al. (2022).(3) |
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