mosquitoID.org

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free artificial intelligence apps to fill global surveillance gaps

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for citizen scientists and mosquito control personnel;

species ID currently focused on the invasive urban malaria vector, Anopheles stephensi

Please note: these AI tools are still in early development, with beta versions to launch July 15, 2022

Sign up for updates below, and for questions, requests, or bugs please email ryancarney[at]usf.edu

CLICK ON A TOOL AND UPLOAD SMARTPHONE PHOTOS*:

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identifies whether Anopheles stephensi or not

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identifies whether unfed, fed, semi-gravid, or gravid (any species)

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larval photos require use of a 60X clip-on lens (at right; see also tip sheet below):

*results from any other camera/microscope images should be considered unreliable

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identifies whether Anopheles stephensi or Anopheles gambiae s.s.

(other species are invalid, for now)

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identifies the anatomy: head, thorax, abdomen, and terminal end

(any species)

Resources and Links

  • demonstration + presentation:  YouTube

  • citizen science GIS map:  launches July 15, 2022

 

Related Publications

Integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes

Carney RM, Mapes C, Low R, Long A, Bowser A, Durieux D, Rivera K, Seltzer C, Dekramanjian B, Bartumeus F, Azam F, Chellappan S, & Palmer, J. Insects (in revision)

 

A framework based on deep neural networks to extract anatomy of mosquitoes from images  pdf

Minakshi M, Bharti P, Bhuiyan T, Kariev S & Chellappan S. 2020. Scientific Reports, 10:13059.

Automating the surveillance of mosquito vectors from trapped specimens using computer vision techniques  pdf

Minakshi M, Bharti P, McClinton III WB, Mirzakhalov J, Carney RM, Chellappan S. 2020. Proceedings of ACM COMPASS 105-115.

Patents Pending

Carney RM, Chellappan S, Morris PJR, Azam F, Rivera K, & Byuiyan T. SYSTEMS AND METHODS FOR CLASSIFYING MOSQUITO LARVAE BASED ON EXTRACTED MASKS OF ANATOMICAL COMPONENTS FROM IMAGES. US 63/140,505; PCT/US22/17089; USF 20A055. International patent application filed 2022-02-18.​

 

Chellappan S, Minakshi M, Bharti P, & Carney RM. SYSTEMS AND METHODS FOR CLASSIFYING MOSQUITOES BASED ON EXTRACTED MASKS OF ANATOMICAL COMPONENTS FROM IMAGES. US 17/462,809; USF 21A015US. Full patent application filed 2021-08-31.

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