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0:00:05 [Talk: Rapid Identification of similar Foodborne Pathogens using Deep Neural network for Raman Spectroscopy]
0:01:04 Outline
0:01:29 Raman Spectroscopy
0:02:38 Why Raman Spectroscopy
0:03:33 Examples of Raman spectra for material Identification
0:04:31 What Information do we get from Raman Spectrum?
0:05:26 Workflow in Raman Spectral Analysis
0:06:04 Case study : Raman Spectroscopic studies on food pathogens
0:07:00 Raman spectrum of bacteria
0:08:14 Using Principal Component Analysis
0:08:30 Raman Spectra of all 8 similar Bacteria samples
0:09:05 Exploratory Data Analysis using PCA
0:09:40 PCA only with 4 bacterial strains
0:10:03 Solution - Deep Learning
0:10:18 Potential use of Deep learning in Biological Raman spectra
0:10:39 Deep Learning workflow
0:11:18 Machine Learning
0:11:37 Convolutional Neural Network (CNN)
0:11:44 CNN Architecture
0:11:51 Convolution Operation
0:12:10 Our Proposed Method
0:12:51 Loss vs Accuracy for trained 60 Raman Spectra
0:13:03 Data visualization in CNN
0:13:19 t-SNE Data Visualization of CNN layers (30 spectra)
0:13:46 Prediction Results
0:14:13 Conclusion
0:14:49 Future Work
0:15:14 Thank you
0:15:33 Q&A

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