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Insecta

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Deep learning and targeted metabolomics-based monitoring of chewing insects in tea plants and screening defense compounds.

Plant, cell & environment
Tea is an important cash crop that is often consumed by chewing pests, resulting in reduced yields and economic losses. It is important to establish a method to quickly identify the degree of damage to tea plants caused by leaf-eating insects and scr...

A Navigation Algorithm to Enable Sustainable Control of Insect-Computer Hybrid Robot with Stimulus Signal Regulator and Habituation-Breaking Function.

Soft robotics
The insect-computer hybrid soft robots are receiving increasing attention due to their excellent motor capabilities, small size, and low power consumption. However, the effective control of insects is limited to minutes since the response from insect...

An annotated wing interferential pattern dataset of dipteran insects of medical interest for deep learning.

Scientific data
Several Diptera species are known to transmit pathogens of medical and veterinary interest. However, identifying these species using conventional methods can be time-consuming, labor-intensive, or expensive. A computer vision-based system that uses W...

The generalized spring-loaded inverted pendulum model for analysis of various planar reduced-order models and for optimal robot leg design.

Bioinspiration & biomimetics
This paper proposes a generalized spring-loaded inverted pendulum (G-SLIP) model to explore various popular reduced-order dynamic models' characteristics and suggest a better robot leg design under specified performance indices. The G-SLIP model's co...

Multiple forces facilitate the aquatic acrobatics of grasshopper and bioinspired robot.

Proceedings of the National Academy of Sciences of the United States of America
Aquatic locomotion is challenging for land-dwelling creatures because of the high degree of fluidity with which the water yields to loads. We surprisingly found that the Chinese rice grasshopper , known for its terrestrial acrobatics, could swiftly l...

An effective segmentation and attention-based reptile residual capsule auto encoder for pest classification.

Pest management science
PURPOSE: Insect pests are a major global factor affecting agricultural crop productivity and quality. Rapid and precise insect pest detection is crucial for improving handling and prediction techniques. There are several methods for pest detection an...

EResNet-SVM: an overfitting-relieved deep learning model for recognition of plant diseases and pests.

Journal of the science of food and agriculture
BACKGROUND: The accurate recognition and early warning for plant diseases and pests are a prerequisite of intelligent prevention and control for plant diseases and pests. As a result of the phenotype similarity of the hazarded plant after plant disea...

Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Automated sensors have potential to standardize and expand the monitoring of insects across the globe. As one of the most scalable and fastest developing sensor technologies, we describe a framework for automated, image-based monitoring of nocturnal ...

Design and control of jumping microrobots with torque reversal latches.

Bioinspiration & biomimetics
Jumping microrobots and insects power their impressive leaps through systems of springs and latches. Using springs and latches, rather than motors or muscles, as actuators to power jumps imposes new challenges on controlling the performance of the ju...

Detection and recognition of the invasive species, Hylurgus ligniperda, in traps, based on a cascaded convolution neural network.

Pest management science
BACKGROUND: Hylurgus ligniperda, an invasive species originating from Eurasia, is now a major forestry quarantine pest worldwide. In recent years, it has caused significant damage in China. While traps have been effective in monitoring and controllin...