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BEGIN:VEVENT
DTSTAMP:20210402T160550Z
LOCATION:Poster Module
DTSTART;TZID=America/New_York:20201119T083000
DTEND;TZID=America/New_York:20201119T170000
UID:submissions.supercomputing.org_SC20_sess341_spostu102@linklings.com
SUMMARY:Automatic Capture and Classification of Frog Calls
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nAutomatic Capture 
 and Classification of Frog Calls\n\nForan, Underwood\n\nGlobal frog popula
 tions are threatened by an increasing number of environmental threats such
  as habitat loss, disease, and pollution. Traditionally, in-person acousti
 c surveys of frogs have measured population loss and conservation outcomes
  among these visually cryptic species. However, these methods rely heavily
  on trained individuals and time-consuming field work. We propose an end-t
 o-end workflow for the automatic recording, presence-absence identificatio
 n, and web page visualization of frog calls by their species. The workflow
  encompasses recording of frog calls via custom Raspberry Pi’s, data-pushi
 ng to Jetstream cloud computer, and species classification by three differ
 ent machine learning models: Random Forest, Convolutional Neural Network, 
 and Recursive Neural Network.\n\nTag: Student Program\n\nRegistration Cate
 gory: Tech Program Reg Pass, Exhibits Reg Pass
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