Figure 4
From: A Swin Transformer-based model for mosquito species identification
Comparison of mosquito recognition effects of computer vision network models and variants. (a) Comparison of mosquito identification accuracy between 3 CNNs and 3 Transformer; (b) The best effect CNN (YOLOv5) training set loss curve(blue), validation set loss curve(green) and validation set accuracy curve(orange); (c) The best effect Transformer (Swin Transformer) training set loss curve, validation set loss curve and validation set accuracy curve. (d) Swin-MSI-T test result confusion matrix; (e) Swin-MSI -B test result confusion matrix; (f) Swin-MSI -L test result confusion matrix. Confusion matrix of mosquito labels in which odd numbers represent females and even numbers represent males. The small squares in the confusion matrix represent the recognition readiness rate, from red to green, the recognition readiness rate is getting higher and higher An. sinensis: 1, 2; Cx. pipiens quinquefasciatus: 3, 4; Cx. pipiens pallens: 5, 6; Cx. pipiens molestus: 7,8 Cx. modestus: 9,10; Ae. albopictus: 11, 12 Ae. aegypti: 13, 14; Cx. pallidothorax: 15, 16 Ae. galloisi: 17,18 Ae. vexans: 19, 20; Ae. koreicus: 21, 22 Armigeres subalbatus: 23, 24; Coquillettidia ochracea: 25, 26 Cx. gelidus: 27, 28 Cx. triraeniorhynchus: 29, 30 Mansonia uniformis: 31, 32 An. vagus: 33, 34 Ae. elsaie: 35,36 Toxorhynchites splendens: 37, 38.
