TruaceTracing the truth around AIWednesday, August 5, 2026
TRV-2026-0654Certified recordPeer-reviewed

SolenopsisDetector: development of an automatic detection system for fire ants using computer vision and deep learning

Fire ants (Solenopsis spp. Westwood) pose a major ecological and economic threat, mainly due to the invasive potential of certain species. Current identification methods are highly dependent on taxonomic expertise, which can slow down decision-making. The development of an automated detection system could therefore support the identification process. We present SolenopsisDetector (SolenopD), an automated system for identifying Solenopsis ants using computer vision and deep learning. Following taxonomic practice,…

Science · G Space — documented gain · certified 2026-08-05 · v1 · article view · machine-readable

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Automated vision system SolenopsisDetector can localize fire ants and classify Solenopsis species from images, with whole-body detection reaching high mAP and thorax/abdomen crops improving classification accuracy.

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Truvace Impact Record TRV-2026-0654, v1: “SolenopsisDetector: development of an automatic detection system for fire ants using computer vision and deep learning.” Truvace, 2026-08-05. /record/TRV-2026-0654 (accessed at citation time). sha256 71bb153e121439fd

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