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Moths

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COVID-19 classification using chest X-ray images: A framework of CNN-LSTM and improved max value moth flame optimization.

Frontiers in public health
Coronavirus disease 2019 (COVID-19) is a highly contagious disease that has claimed the lives of millions of people worldwide in the last 2 years. Because of the disease's rapid spread, it is critical to diagnose it at an early stage in order to redu...

Human Gait Analysis: A Sequential Framework of Lightweight Deep Learning and Improved Moth-Flame Optimization Algorithm.

Computational intelligence and neuroscience
Human gait recognition has emerged as a branch of biometric identification in the last decade, focusing on individuals based on several characteristics such as movement, time, and clothing. It is also great for video surveillance applications. The ma...

Reflectance spectroscopy and machine learning as a tool for the categorization of twin species based on the example of the Diachrysia genus.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In our work we used noninvasive point reflectance spectroscopy in the range from 400 to 2100 nm coupled with machine learning to study scales on the brown and golden iridescent areas on the dorsal side of the forewing of Diachrysia chrysitis and D. s...

Robust Moth-Inspired Algorithm for Odor Source Localization Using Multimodal Information.

Sensors (Basel, Switzerland)
Odor-source localization, by which one finds the source of an odor by detecting the odor itself, is an important ability to possess in order to search for leaking gases, explosives, and disaster survivors. Although many animals possess this ability, ...

A novel method for identifying key genes in macroevolution based on deep learning with attention mechanism.

Scientific reports
Macroevolution can be regarded as the result of evolutionary changes of synergistically acting genes. Unfortunately, the importance of these genes in macroevolution is difficult to assess and hence the identification of macroevolutionary key genes is...

Monitoring the leaf damage by the rice leafroller with deep learning and ultra-light UAV.

Pest management science
BACKGROUND: Rice leafroller is a serious threat to the production of rice. Monitoring the damage caused by rice leafroller is essential for effective pest management. Owing to limitations in collecting decent quality images and high-performing identi...

Multibody system dynamics for bio-robotic design and simulation based on inching-locomotion caterpillar's gait: MBD-ILAR method.

Bioinspiration & biomimetics
Inching-locomotion caterpillars (ILAR) inspire the design of 'inch-worm' robots with biomimicry features, that can be adapted to different environments, such as natural, man-made, or other planets. Therefore, this work defines a novel mathematical me...

Instar identification and weight prediction of (Guenée) larvae using machine learning.

Bulletin of entomological research
The Asian corn borer, (Guenée), emerges as a significant threat to maize cultivation, inflicting substantial damage upon the crops. Particularly, its larval stage represents a critical point characterised by significant economic consequences on maiz...

Testing the equivalency of human "predators" and deep neural networks in the detection of cryptic moths.

Journal of evolutionary biology
Researchers have shown growing interest in using deep neural networks (DNNs) to efficiently test the effects of perceptual processes on the evolution of colour patterns and morphologies. Whether this is a valid approach remains unclear, as it is unkn...

Insight into the Relationships Between Chemical, Protein and Functional Variables in the PBP/GOBP Family in Moths Based on Machine Learning.

International journal of molecular sciences
During their lives, insects must cope with a plethora of chemicals, of which a few will have an impact at the behavioral level. To detect these chemicals, insects use several protein families located in their main olfactory organs, the antennae. Insi...