  Portuguese man-of-war (PMW) is a gelatinous organism with long tentacles
capable of causing severe burns, thus leading to negative impacts on human
activities, such as tourism and fishing. There is a lack of information about
the spatio-temporal dynamics of this species. Therefore, the use of alternative
methods for collecting data can contribute to their monitoring. Given the
widespread use of social networks and the eye-catching look of PMW, Instagram
posts can be a promising data source for monitoring. The first task to follow
this approach is to identify posts that refer to PMW. This paper reports on the
use of convolutional neural networks for PMW images classification, in order to
automate the recognition of Instagram posts. We created a suitable dataset, and
trained three different neural networks: VGG-16, ResNet50, and InceptionV3,
with and without a pre-trained step with the ImageNet dataset. We analyzed
their results using accuracy, precision, recall, and F1 score metrics. The
pre-trained ResNet50 network presented the best results, obtaining 94% of
accuracy and 95% of precision, recall, and F1 score. These results show that
convolutional neural networks can be very effective for recognizing PMW images
from the Instagram social media.
