Emerging technologies revolutionise insect ecology and monitoring

R Van Klink, T August, Y Bas, P Bodesheim… - Trends in ecology & …, 2022 - cell.com
Insects are the most diverse group of animals on Earth, but their small size and high diversity
have always made them challenging to study. Recent technological advances have the …

Towards the fully automated monitoring of ecological communities

M Besson, J Alison, K Bjerge, TE Gorochowski… - Ecology …, 2022 - Wiley Online Library
High‐resolution monitoring is fundamental to understand ecosystems dynamics in an era of
global change and biodiversity declines. While real‐time and automated monitoring of …

Accurate detection and identification of insects from camera trap images with deep learning

K Bjerge, J Alison, M Dyrmann… - PLOS Sustainability …, 2023 - journals.plos.org
Reported insect declines have dramatically increased the global demand for standardized
insect monitoring data. Image-based monitoring can generate such data cost-efficiently and …

Multimodal brain tumor segmentation and classification from MRI scans based on optimized DeepLabV3+ and interpreted networks information fusion empowered …

MS Ullah, MA Khan, HM Albarakati… - Computers in Biology …, 2024 - Elsevier
Explainable artificial intelligence (XAI) aims to offer machine learning (ML) methods that
enable people to comprehend, properly trust, and create more explainable models. In …

[HTML][HTML] Brain tumor classification from MRI scans: a framework of hybrid deep learning model with Bayesian optimization and quantum theory-based marine predator …

MS Ullah, MA Khan, A Masood, O Mzoughi… - Frontiers in …, 2024 - frontiersin.org
Brain tumor classification is one of the most difficult tasks for clinical diagnosis and treatment
in medical image analysis. Any errors that occur throughout the brain tumor diagnosis …

Eyes on nature: Embedded vision cameras for terrestrial biodiversity monitoring

KFA Darras, M Balle, W Xu, Y Yan… - Methods in Ecology …, 2024 - Wiley Online Library
We need comprehensive information to manage and protect biodiversity in the face of global
environmental challenges, and artificial intelligence is required to generate that information …

Moths complement bumblebee pollination of red clover: a case for day-and-night insect surveillance

J Alison, JM Alexander, N Diaz Zeugin… - Biology …, 2022 - royalsocietypublishing.org
Recent decades have seen a surge in awareness about insect pollinator declines. Social
bees receive the most attention, but most flower-visiting species are lesser known, non-bee …

[HTML][HTML] Computer vision and deep learning in insects for food and feed production: A review

S Nawoya, F Ssemakula, R Akol, Q Geissmann… - … and Electronics in …, 2024 - Elsevier
Commercial insect production is a relatively new field that has gained traction in recent
years due to its potential as a sustainable source of protein. Despite its promising future, the …

A Deep-Learning-Based detection approach for the identification of insect species of economic importance

M Tannous, C Stefanini, D Romano - Insects, 2023 - mdpi.com
Simple Summary This study aims at develo** a machine-learning-based classification
approach to recognize insect species of economic importance. Two tephritid pest species …

[HTML][HTML] Hierarchical classification of insects with multitask learning and anomaly detection

K Bjerge, Q Geissmann, J Alison, HMR Mann… - Ecological …, 2023 - Elsevier
Cameras and computer vision are revolutionising the study of insects, creating new research
opportunities within agriculture, epidemiology, evolution, ecology and monitoring of …