A survey on image-based insect classification

Abstract

International audienceEntomology has had many applications in many biological domains (i.e insect counting as a biodiversity index). To meet a growing biological demand and to compensate a decreasing workforce amount, automated entomology has been around for decades. This challenge has been tackled by computer scientists as well as by biologists themselves. This survey investigates fourty-four studies on this topic and tries to give a global picture on what are the scientific locks and how the problem was addressed. Views are adopted on image capture, feature extraction, classification methods and the tested datasets. A general discussion is finally given on the questions that might still remain unsolved such as: the image capture conditions mandatory to good recognition performance, the definition of the problem and whether computer scientist should consider it as a problem in its own or just as an instance of a wider image recognition problem

Species‐level image classification with convolutional neural network enables insect identification from habitus images

“…Comparing our results to those obtained from other convolutional neural networks, built for the specific purpose of identifying other groups of arthropods (e.g.,Marques et al, 2018), there is scope for increasing both classification recall and taxonomic resolution.Either image quality, network structure, number of classes to predict, or the image recording perspective could explain the differences.When comparing precision and accuracy of dorsal perspective images of ants byMarques et al (2018) we achieve comparable results (precision 54.7% and balanced accuracy 75.3% vs. 52.0% and 59.0%).For a range of other studies that classify arthropods to species level, the results are comparable, even though fewer species are typically used in classification(Martineau et al, 2017). van Horn et al(2017) presented a species level trained network based on Inception ResNet v2 and 675,000 images among 5,000 species of plants and animals.…”

“…Image classifications used for species identification have dramatically increased in accuracy, performance, and in the number of taxa analyzed (Marques et al, 2018;Martineau et al, 2017;Norouzzadeh et al, 2018;Schneider, Taylor, & Kremer, 2018;Van Horn et al, 2017).…”

Thinking like a naturalist: enhancing computer vision of citizen science images by harnessing contextual data

“…Identification of insects poses a considerable challenge for computer vision (Martineau et al, 2017). 468…”

Sensing Technologies used for Monitoring and Detecting Insect Infestation in Stored Grain

“…A comprehensive study is done in [38] on image based insect classification. This study discussed on type of images, how to extract feature with different methods and classification methods with their issues and database.…”