title: Flying insect detection and classification with inexpensive sensors.
abstract: An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect's flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.
authors.affiliation: Department of Computer Science and Engineering, University of California, Riverside; ychen053@ucr.edu.
authors.forename: Yanping
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Department of Entomology, University of California, Riverside.
authors.forename: Adena
authors.initials: A
authors.lastname: Why
authors.affiliation: Institute of Mathematics and Computer Sciences, University of São Paulo - USP.
authors.forename: Gustavo
authors.initials: G
authors.lastname: Batista
authors.affiliation: ISCA Technologies.
authors.forename: Agenor
authors.initials: A
authors.lastname: Mafra-Neto
authors.affiliation: Department of Computer Science and Engineering, University of California, Riverside.
authors.forename: Eamonn
authors.initials: E
authors.lastname: Keogh
mesh_terms: D000162:Acoustics; D000330:Aedes / Q000502:physiology*; D000818:Animals; D003465:Culex / Q000502:physiology*; D004772:Entomology / Q000295:instrumentation / Q000379:methods*; D005260:Female; D005426:Flight, Animal / Q000502:physiology*; D008297:Male; D055095:Optics and Photonics / Q000295:instrumentation / Q000379:methods*; D012984:Software