Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151400
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dc.contributor.authorQiu, Ruidien_US
dc.date.accessioned2021-06-17T07:30:28Z-
dc.date.available2021-06-17T07:30:28Z-
dc.date.issued2021-
dc.identifier.citationQiu, R. (2021). High-throughput neuron fluorescence imaging through artificial intelligence. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/151400en_US
dc.identifier.urihttps://hdl.handle.net/10356/151400-
dc.description.abstractFluorescence image analysis is a commonly used method in biological image processing. In practice, different dyes correspond to different staining structures inside the cell. It is difficult for us to manually analyze and correlate images, as it is a tedious process and image interpretation is subjective from person to person. Deep learning has proven to be successful in image classification field. In recent years, it has been widely used in the field of biological image analysis. This project will start from the processing of fluorescence image to tuning parameter of designed convolution neural network. The goal of this project is to build a deep learning model to classify different types of neuron cells for biomedical detection.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Electrical and electronic engineering::Electronic systems::Biometricsen_US
dc.subjectEngineering::Electrical and electronic engineering::Electronic systems::Signal processingen_US
dc.titleHigh-throughput neuron fluorescence imaging through artificial intelligenceen_US
dc.typeThesis-Master by Courseworken_US
dc.contributor.supervisorY. C. Chenen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Signal Processing)en_US
dc.contributor.researchCentre for Biodevices and Bioinfomaticsen_US
dc.contributor.supervisoremailyucchen@ntu.edu.sgen_US
item.grantfulltextembargo_restricted_20221231-
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