Abstract: A detection device for detecting the presence of a substance of interest in a sample is described. The device can include a data store comprising executable instructions for at least one convolutional neural network, CNN, configured to process images: and a processor coupled to the data store and configured to execute the instructions to operate the at least one CNN. The detection device can be configured to: obtain spectrometry data, operate a first one of the CNNs to process the spectrometry data to obtain a first CNN output; apply a mask to the spectrometry data to obtain masked data; operate a second one of the CNNs to process the masked data to obtain a second CNN output; and determine if the substance of interest is present in the sample based on both the first CNN output and the second CNN output.

Abstract: A detection device for detecting the presence of a substance of interest in a sample is described. The device can include a data store comprising executable instructions for at least one convolutional neural network, CNN, configured to process images: and a processor coupled to the data store and configured to execute the instructions to operate the at least one CNN. The detection device can be configured to: obtain spectrometry data, operate a first one of the CNNs to process the spectrometry data to obtain a first CNN output; apply a mask to the spectrometry data to obtain masked data; operate a second one of the CNNs to process the masked data to obtain a second CNN output; and determine if the substance of interest is present in the sample based on both the first CNN output and the second CNN output.

Abstract: A detection device for detecting the presence of a substance of interest in a sample is described. The device can include a data store comprising executable instructions for at least one convolutional neural network, CNN, configured to process images: and a processor coupled to the data store and configured to execute the instructions to operate the at least one CNN. The detection device can be configured to: obtain spectrometry data, operate a first one of the CNNs to process the spectrometry data to obtain a first CNN output; apply a mask to the spectrometry data to obtain masked data; operate a second one of the CNNs to process the masked data to obtain a second CNN output; and determine if the substance of interest is present in the sample based on both the first CNN output and the second CNN output.

Abstract: A detection device for detecting the presence of a substance of interest in a sample is described. The device can include a data store comprising executable instructions for at least one convolutional neural network, CNN, configured to process images: and a processor coupled to the data store and configured to execute the instructions to operate the at least one CNN. The detection device can be configured to: obtain spectrometry data, operate a first one of the CNNs to process the spectrometry data to obtain a first CNN output; apply a mask to the spectrometry data to obtain masked data; operate a second one of the CNNs to process the masked data to obtain a second CNN output; and determine if the substance of interest is present in the sample based on both the first CNN output and the second CNN output.