AIMC Topic: Animals

Clear Filters Showing 1491 to 1500 of 8866 articles

Bio-inspired two-stage network for efficient RGB-D salient object detection.

Neural networks : the official journal of the International Neural Network Society
Recently, with the development of the Convolutional Neural Network and Vision Transformer, the detection accuracy of the RGB-D salient object detection (SOD) model has been greatly improved. However, most of the existing methods cannot balance comput...

Machine learning predicts selected cat diseases using insurance data amid challenges in interpretability.

American journal of veterinary research
OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insurance data and to evaluate their predictive performance.

Application of artificial intelligence and machine learning in bovine respiratory disease prevention, diagnosis, and classification.

American journal of veterinary research
Bovine respiratory disease (BRD) is the leading infectious disease in cattle, resulting in significant economic losses and welfare concerns in beef and dairy production systems. Traditional diagnostic methods for BRD typically rely on clinical observ...

Machine Learning-Driven Discovery of Structurally Related Natural Products as Activators of the Cardiac Calcium Pump SERCA2a.

ChemMedChem
A key molecular dysfunction in heart failure is the reduced activity of the cardiac sarcoplasmic reticulum Ca-ATPase (SERCA2a) in cardiac muscle cells. Reactivating SERCA2a improves cardiac function in heart failure models, making it a validated targ...

Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.

Journal of food protection
While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to help improve food safety, the development and deployment of these models in the food safety domain are by and large lacking. The absence of publicly a...

Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging.

Sensors (Basel, Switzerland)
Ensuring the safety and quality of poultry products requires efficient detection and removal of foreign materials during processing. Hyperspectral imaging (HSI) offers a non-invasive mechanism to capture detailed spatial and spectral information, ena...

Discovery of TRPV4-Targeting Small Molecules with Anti-Influenza Effects Through Machine Learning and Experimental Validation.

International journal of molecular sciences
Transient receptor potential vanilloid 4 (TRPV4) is a calcium-permeable cation channel critical for maintaining intracellular Ca homeostasis and is essential in regulating immune responses, metabolic processes, and signal transduction. Recent studies...

Unveiling the new chapter in nanobody engineering: advances in traditional construction and AI-driven optimization.

Journal of nanobiotechnology
Nanobodies (Nbs), miniature antibodies consisting solely of the variable region of heavy chains, exhibit unique properties such as small size, high stability, and strong specificity, making them highly promising for disease diagnosis and treatment. T...

Analysis of Operant Self-administration Behaviors with Supervised Machine Learning: Protocol for Video Acquisition and Pose Estimation Analysis Using DeepLabCut and Simple Behavioral Analysis.

eNeuro
The use of supervised machine learning to approximate poses in video recordings allows for rapid and efficient analysis of complex behavioral profiles. Currently, there are limited protocols for automated analysis of operant self-administration behav...

Reconstruction of Adaptive Leaky Integrate-and-Fire Neuron to Enhance the Spiking Neural Networks Performance by Establishing Complex Dynamics.

IEEE transactions on neural networks and learning systems
Since digital spiking signals can carry rich information and propagate with low computational consumption, spiking neural networks (SNNs) have received great attention from neuroscientists and are regarded as the future development object of neural n...