AIMC Topic: Animals

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Leveraging social media and deep learning to detect rare megafauna in video surveys.

Conservation biology : the journal of the Society for Conservation Biology
Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys p...

Early pregnancy diagnosis of rabbits: A non-invasive approach using Vis-NIR spatially resolved spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Pregnancy diagnosis is essential for rabbit's reproductive management. The early identification of non-pregnant rabbits allows for earlier re-insemination, increases the service rate, and reduces the laboring interval in commercial operations. The ob...

AI Enabled IoRT Framework for Rodent Activity Monitoring in a False Ceiling Environment.

Sensors (Basel, Switzerland)
Routine rodent inspection is essential to curbing rat-borne diseases and infrastructure damages within the built environment. Rodents find false ceilings to be a perfect spot to seek shelter and construct their habitats. However, a manual false ceili...

A concise review: the synergy between artificial intelligence and biomedical nanomaterials that empowers nanomedicine.

Biomedical materials (Bristol, England)
Nanomedicine has recently experienced unprecedented growth and development. However, the complexity of operations at the nanoscale introduces a layer of difficulty in the clinical translation of nanodrugs and biomedical nanotechnology. This problem i...

LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals.

Nature methods
Markerless three-dimensional (3D) pose estimation has become an indispensable tool for kinematic studies of laboratory animals. Most current methods recover 3D poses by multi-view triangulation of deep network-based two-dimensional (2D) pose estimate...

Development of a deep learning model from breeding substrate images: a novel method for estimating the abundance of house fly (Musca domestica L.) larvae.

Pest management science
BACKGROUND: The application of computer vision and deep learning to pest monitoring has recently received much attention. Although several studies have demonstrated the application of object detection to the number of pests on a substrate, for house ...

Deep-learning-based motion correction in optical coherence tomography angiography.

Journal of biophotonics
Optical coherence tomography angiography (OCTA) is a widely applied tool to image microvascular networks with high spatial resolution and sensitivity. Due to limited imaging speed, the artifacts caused by tissue motion can severely compromise visuali...

Skilled reach training enhances robotic gait training to restore overground locomotion following spinal cord injury in rats.

Behavioural brain research
Rehabilitative training has been shown to improve motor function following spinal cord injury (SCI). Unfortunately, these gains are primarily task specific; where reach training only improves reaching, step training only improves stepping and stand t...

Bioacoustic classification of avian calls from raw sound waveforms with an open-source deep learning architecture.

Scientific reports
The use of autonomous recordings of animal sounds to detect species is a popular conservation tool, constantly improving in fidelity as audio hardware and software evolves. Current classification algorithms utilise sound features extracted from the r...

A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging.

Nature neuroscience
Inference of action potentials ('spikes') from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals ('ground truth'). In this study, we compiled a large, diverse ground truth da...