The analysis of the field traps where the mosquitoes insert their eggs is
vital to check that the sterile insect technique (SIT) is working properly.
This is because the number of hatched eggs may indicate that the sterile males
are not competing with the wild ones. Nowadays, the study of the traps is done
manually by microscope and is very time-consuming and prone to human error.
This paper presents an automatic trap survey. For this purpose, a device has
been designed that automatically scans the slat obtaining different overlapping
photos. Subsequently, the images are analyzed by a Mask-RCNN neural network
that segments the eggs and classifies them into 2 classes: full or hatch

这篇论文介绍了一种自动陷阱调查方法，通过设计的装置对蛾子产卵地进行自动扫描，然后利用 Mask-RCNN 神经网络对图像进行分割和分类来分析鸟蛋是否孵化。

田间捕蚊器中蚊卵的自动计数和分类

Automatic Counting and Classification of Mosquito Eggs in Field Traps

The Sterile Insect Technique (SIT) is a biological pest control technique
based on the release into the environment of sterile males of the insect
species whose population is to be controlled. The entire SIT process involves
mass-rearing within a biofactory, sorting of the specimens by sex,
sterilization, and subsequent release of the sterile males into the
environment. The reason for avoiding the release of female specimens is
because, unlike males, females bite, with the subsequent risk of disease
transmission. In the case of Aedes mosquito biofactories for SIT, the key point
of the whole process is sex separation. This process is nowadays performed by a
combination of mechanical devices and AI-based vision systems. However, there
is still a possibility of false negatives, so a last stage of verification is
necessary before releasing them into the environment. It is known that the
sound produced by the flapping of adult male mosquitoes is different from that
produced by females, so this feature can be used to detect the presence of
females in containers prior to environmental release. This paper presents a
study for the detection of females in Aedes mosquito release vessels for SIT
programs. The containers used consist of PVC a tubular design of 8.8cm diameter
and 12.5cm height. The containers were placed in an experimental setup that
allowed the recording of the sound of mosquito flight inside of them. Each
container was filled with 250 specimens considering the cases of (i) only male
mosquitoes, (ii) only female mosquitoes, and (iii) 75% males and 25% females.
Case (i) was used for training and testing, whereas cases (ii) and (iii) were
used only for testing. Two algorithms were implemented for the detection of
female mosquitoes: an unsupervised outlier detection algorithm (iForest) and a
one-class SVM trained with male-only recordings.

本研究提出了一种通过声音检测异育交蚊容器中雌蚊的方法，以在无人监视的情况下进行艾德斯蚊进行无菌雄性释放计划