AIMC Topic: Animals

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Deep learning workflow to support in-flight processing of digital aerial imagery for wildlife population surveys.

PloS one
Deep learning shows promise for automating detection and classification of wildlife from digital aerial imagery to support cost-efficient remote sensing solutions for wildlife population monitoring. To support in-flight orthorectification and machine...

A deep learning-based approach for fully automated segmentation and quantitative analysis of muscle fibers in pig skeletal muscle.

Meat science
Muscle fiber properties exert a significant influence on pork quality, with cross-sectional area (CSA) being a crucial parameter closely associated with various meat quality indicators, such as shear force. Effectively identifying and segmenting musc...

Dynamics of changes in broiler spatial distribution induced by a robot with autonomous navigation along the growing cycle.

Poultry science
Welfare problems in broiler chickens are associated with accelerated growth in high density and barren environments. Encouraging broiler movement yields benefits by increasing locomotion, foraging, and environmental exploration. Robot sensors with au...

Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation.

PloS one
Individual muscle segmentation is the process of partitioning medical images into regions representing each muscle. It can be used to isolate spatially structured quantitative muscle characteristics, such as volume, geometry, and the level of fat inf...

Electro-Thermopneumatically Actuated, Adhesion-Force Controllable Octopus-Like Suction Cup Actuator.

Soft robotics
A light-weight actuator developed in this work belongs to a class of soft robots, and in a sense, resembles an octopus. Its main function is in the attachment or detachment to a solid surface driven by an electro-thermopneumatic mechanism. In this st...

Insights into the transformation of natural organic matter during UV/peroxydisulfate treatment by FT-ICR MS and machine learning: Non-negligible formation of organosulfates.

Water research
Natural organic matter (NOM) is a major sink of radicals in advanced oxidation processes (AOPs) and understanding the transformation of NOM is important in water treatment. By using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR ...

Application of computer vision and deep learning models to automatically classify medically important mosquitoes in North Borneo, Malaysia.

Bulletin of entomological research
Mosquito-borne diseases have emerged in North Borneo in Malaysia due to rapid changes in the forest landscape, and mosquito surveillance is key to understanding disease transmission. However, surveillance programmes involving sampling and taxonomic i...

Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning.

Meat science
Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns...

The ERUS course on robot-assisted kidney transplantation.

World journal of urology
PURPOSE: Robot-assisted kidney transplantation (RAKT) is being increasingly performed at selected referral institutions worldwide. Yet, surgical training in RAKT is still unstructured and not grounded into formal credentialing courses including simul...

Remote and low-cost intraocular pressure monitoring by deep learning of speckle patterns.

Journal of biomedical optics
SIGNIFICANCE: Glaucoma, a leading cause of global blindness, disproportionately affects low-income regions due to expensive diagnostic methods. Affordable intraocular pressure (IOP) measurement is crucial for early detection, especially in low- and m...