ITS Meeting December 11, 2018

	▪	Project status
	⁃	Monique presented paper at Ocean Sciences
	⁃	ITS -> Data TAG - ITS/CANON/ESP
	⁃	Storage technologies
	⁃	Data Export
	⁃	Technology Export
	▪	2019 Proposal
	⁃	Final Year
	⁃	Feedback: "It is our understanding that Edgington/Cline et al. have made good progress in using machine learning to identify a number of animals in video feeds that were highlighted as key species in earlier versions of this proposal. What has become of that advancement?"
	⁃	Response: “The machine learning work targeting the ITS key species did indeed show very promising results. Duane and Danelle have outlined the detailed results of the ITS key species exploration work in the 2018 and 2019 proposals showing the results of their work and collaborations.  This is an excerpt from that text:
		
		"Classification accuracy was between 62 and 100 percent for key ITS benthic and midwater using training images from the Deep-Sea-Guide and Dallas Hollis 2016 summer intern data"
		
		With this success there are plans to examine the possible integration of these automated methods with the work being done in the Smith Lab. The new Smith Lab postdoc, Jen Durden, is interested in machine learning and will likely be working with Duane and Danelle towards partially automating the annotation of benthic transects.  In addition, the models and lessons learned from the ITS key species exploration will certainly be utilized in the workplan being articulated in the Video TAG proposal.”
	⁃	Three main deliverables
	⁃	Carbon budget shortcomings report and future recommendations
	⁃	data (parameters)
	⁃	methods/technologies
	⁃	Monique to refine analysis and results
	⁃	Code will end up in central repository (actually is there now)
	⁃	Paper to complete reporting of results on work presented at Ocean Sciences
	⁃	Central data repository
	⁃	Using Monique’s algorithms
	⁃	Goal is to have it continually updated as time moves on
	⁃	Using same infrastructure that will be used in CANON, ESP and Data TAG (focus on export)

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