AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Moths

Showing 11 to 19 of 19 articles

Clear Filters

Biocontrol potential of Halotolerant bacterial chitinase from high yielding novel Bacillus Pumilus MCB-7 autochthonous to mangrove ecosystem.

Pesticide biochemistry and physiology
The multifaceted role of chitinase in medicine, agriculture, environmental remediation and various other industries greatly demands the isolation of high yielding chitinase producing microorganisms with improved properties. The current study aimed to...

An improved quasi-steady aerodynamic model for insect wings that considers movement of the center of pressure.

Bioinspiration & biomimetics
A quasi-steady aerodynamic model in consideration of the center of pressure (C.P.) was developed for insect flight. A dynamically scaled-up robotic hawkmoth wing was used to obtain the translational lift, drag, moment and rotational force coefficient...

Mapping the Potential Global Codling Moth (Cydia pomonella L.) Distribution Based on a Machine Learning Method.

Scientific reports
The spread of invasive species may pose great threats to the economy and ecology of a region. The codling moth (Cydia pomonella L.) is one of the 100 worst invasive alien species in the world and is the most destructive apple pest. The economic losse...

Analysis of the role of wind information for efficient chemical plume tracing based on optogenetic silkworm moth behavior.

Bioinspiration & biomimetics
Many animals use olfactory information to search for feeding areas and other individuals in real time and with high efficiency. We focus on the chemical plume tracing (CPT) ability of male silkworm moths and investigate an efficient CPT strategy for ...

Putting a bug in ML: The moth olfactory network learns to read MNIST.

Neural networks : the official journal of the International Neural Network Society
We seek to (i) characterize the learning architectures exploited in biological neural networks for training on very few samples, and (ii) port these algorithmic structures to a machine learning context. The moth olfactory network is among the simples...

Dropping Counter: A Detection Algorithm for Identifying Odour-Evoked Responses from Noisy Electroantennograms Measured by a Flying Robot.

Sensors (Basel, Switzerland)
The electroantennogram (EAG) is a technique used for measuring electrical signals from the antenna of an insect. Its rapid response time, quick recovery speed, and high sensitivity make it suitable for odour-tracking tasks employing mobile robots. Ho...

Artificial intelligence reveals environmental constraints on colour diversity in insects.

Nature communications
Explaining colour variation among animals at broad geographic scales remains challenging. Here we demonstrate how deep learning-a form of artificial intelligence-can reveal subtle but robust patterns of colour feature variation along an ecological gr...

Automatic tracking of free-flying insects using a cable-driven robot.

Science robotics
Flying insects have evolved to develop efficient strategies to navigate in natural environments. Yet, studying them experimentally is difficult because of their small size and high speed of motion. Consequently, previous studies were limited to tethe...

An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning.

Sensors (Basel, Switzerland)
Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the ...