mosquitoID.org

USF.png
NSF.png

free artificial intelligence apps to fill global surveillance gaps

CDC logo 1_transparent.png

...for citizen scientists and mosquito control personnel.

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

Please note that these AI tools are beta versions in early development.

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*:

adult.png

identifies whether Anopheles stephensi or not

adult.png

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

60X lens.jpg

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

larva.png

identifies whether Anopheles stephensi or not (i.e., An. arabiensisAn. gambiae s.s.other species are invalid, for now)

larva.png

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

(any species)

Resources and Links

  • demonstration + presentation:  YouTube

 

Related Publications

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

Carney RM, Mapes C, Low RD, Long A, Bowser A, Durieux D, Rivera K, Dekramanjian B, Bartumeus F, Guerrero D, Seltzer CE, Azam F, Chellappan S, Palmer JRB. 2022. Insects 13(8):675. Special issue, "Citizen science approaches to vector surveillance"

 

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.

Sign up for future updates and releases

Name

Email

Figure 5.png