Research graph
References from Measurement of water pollution concentration using machine learning in a microchannel-based common-path interferometer. Local targets link to admitted publications; unresolved targets remain external evidence.
Particle separation and sorting in microfluidic devices: a review
10.1007/s10404-013-1291-9 · 2014 · External reference
Combining machine learning and Mie theory to simplify particle characterization inside microchannels
10.1063/5.0157486 · 2023 · External reference
Influence of concentration and flow rate on the birefringence of graphene oxide liquid crystals in microchannels
10.1364/oe.574505 · 2025 · External reference
Birefringent graphene oxide liquid crystals in microchannel for optical switch
10.1021/acsanm.9b02469 · 2020 · External reference
Microfluidic tuning of linear and nonlinear absorption in graphene oxide liquid crystals
10.1364/ol.408816 · 2021 · External reference
Water pollution 'timebomb' threatens global health
10.1038/d41586-023-02337-7 · 2023 · External reference
Simultaneous determination of Ba, Co, Fe, and Ni in nuts by high-resolution continuum source atomic absorption spectrometry after extraction induced by solid-oil-water emulsion breaking
2021 · External reference
Tandem mass spectrometry enhances the performances of pyrolysis-gas chromatography-mass spectrometry for microplastic quantification
10.1016/j.jaap.2023.105993 · 2023 · External reference
Water characterization and early contamination detection in highly varying stochastic background water, based on Machine Learning methodology for processing real-time UV-spectrophotometry
10.1016/j.watres.2019.02.027 · 2019 · External reference
Database-driven screening of South African surface water and the targeted detection of pharmaceuticals using liquid chromatography-high resolution mass spectrometry
10.1016/j.envpol.2017.06.043 · 2017 · External reference
Artificial intelligence-based microfluidic platform for detecting contaminants in water: A review
10.3390/s24134350 · 2024 · External reference
Stable and simple quantitative phase-contrast imaging by Fresnel biprism
10.1063/1.5021008 · 2018 · External reference
Unresolved reference
External reference
Convolutional neural networks: a survey
10.3390/computers12080151 · 2023 · External reference
A review of convolutional neural networks in computer vision
10.1007/s10462-024-10721-6 · 2024 · External reference
Unresolved reference
External reference
An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: methods, challenges, and future works
10.1016/j.compbiomed.2022.106053 · 2022 · External reference
An improved VGG16 model for pneumonia image classification
10.3390/app112311185 · 2021 · External reference
Application analysis of computer vision and image recognition based on improved VGG16 network
10.1007/s42452-025-07471-7 · 2025 · External reference
Imagenet: A large-scale hierarchical image database
2009 · External reference
How transferable are features in deep neural networks?
2014 · External reference
Deep learning
10.1038/nature14539 · 2015 · External reference
Visualizing and understanding convolutional networks
2014 · External reference
A survey on transfer learning
10.1109/tkde.2009.191 · 2009 · External reference
CNN features off-the-shelf: an astounding baseline for recognition
2014 · External reference
Deepsim: deep learning code functional similarity
2018 · External reference
Unresolved reference
2006 · External reference
A review of K-mean algorithm
2013 · External reference
Particle separation and sorting in microfluidic devices: a review
10.1007/s10404-013-1291-9 · ExternalCitation · doi-reference
A review of convolutional neural networks in computer vision
10.1007/s10462-024-10721-6 · ExternalCitation · doi-reference
Application analysis of computer vision and image recognition based on improved VGG16 network
10.1007/s42452-025-07471-7 · ExternalCitation · doi-reference
An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: methods, challenges, and future works
10.1016/j.compbiomed.2022.106053 · ExternalCitation · doi-reference
Database-driven screening of South African surface water and the targeted detection of pharmaceuticals using liquid chromatography-high resolution mass spectrometry
10.1016/j.envpol.2017.06.043 · ExternalCitation · doi-reference
Tandem mass spectrometry enhances the performances of pyrolysis-gas chromatography-mass spectrometry for microplastic quantification
10.1016/j.jaap.2023.105993 · ExternalCitation · doi-reference
Water characterization and early contamination detection in highly varying stochastic background water, based on Machine Learning methodology for processing real-time UV-spectrophotometry
10.1016/j.watres.2019.02.027 · ExternalCitation · doi-reference
Birefringent graphene oxide liquid crystals in microchannel for optical switch
10.1021/acsanm.9b02469 · ExternalCitation · doi-reference
Water pollution 'timebomb' threatens global health
10.1038/d41586-023-02337-7 · ExternalCitation · doi-reference
Deep learning
10.1038/nature14539 · ExternalCitation · doi-reference
Stable and simple quantitative phase-contrast imaging by Fresnel biprism
10.1063/1.5021008 · ExternalCitation · doi-reference
Combining machine learning and Mie theory to simplify particle characterization inside microchannels
10.1063/5.0157486 · ExternalCitation · doi-reference
A survey on transfer learning
10.1109/tkde.2009.191 · ExternalCitation · doi-reference
Influence of concentration and flow rate on the birefringence of graphene oxide liquid crystals in microchannels
10.1364/oe.574505 · ExternalCitation · doi-reference
Microfluidic tuning of linear and nonlinear absorption in graphene oxide liquid crystals
10.1364/ol.408816 · ExternalCitation · doi-reference
An improved VGG16 model for pneumonia image classification
10.3390/app112311185 · ExternalCitation · doi-reference
Convolutional neural networks: a survey
10.3390/computers12080151 · ExternalCitation · doi-reference
Artificial intelligence-based microfluidic platform for detecting contaminants in water: A review
10.3390/s24134350 · ExternalCitation · doi-reference
