AIMC Topic: Horses

Clear Filters Showing 21 to 30 of 70 articles

Comparison of Sysmex XN-V body fluid mode and deep-learning-based quantification with manual techniques for total nucleated cell count and differential count for equine bronchoalveolar lavage samples.

BMC veterinary research
BACKGROUND: Bronchoalveolar lavage (BAL) is a diagnostic method for the assessment of the lower respiratory airway health status in horses. Differential cell count and sometimes also total nucleated cell count (TNCC) are routinely measured by time-co...

Deep learning model shows promise for detecting and grading sesamoiditis in horse radiographs.

American journal of veterinary research
OBJECTIVE: The objective of this study was to develop a robust machine-learning approach for efficient detection and grading of sesamoiditis in horses using radiographs, specifically in data-limited conditions.

Comparing Inertial Measurement Units to Markerless Video Analysis for Movement Symmetry in Quarter Horses.

Sensors (Basel, Switzerland)
BACKGROUND: With an increasing number of systems for quantifying lameness-related movement asymmetry, between-system comparisons under non-laboratory conditions are important for multi-centre or referral-level studies. This study compares an artifici...

Detecting SNP markers discriminating horse breeds by deep learning.

Scientific reports
The assignment of an individual to the true population of origin using a low-panel of discriminant SNP markers is one of the most important applications of genomic data for practical use. The aim of this study was to evaluate the potential of differe...

Machine Learning-Based Sensor Data Fusion for Animal Monitoring: Scoping Review.

Sensors (Basel, Switzerland)
The development of technology, such as the Internet of Things and artificial intelligence, has significantly advanced many fields of study. Animal research is no exception, as these technologies have enabled data collection through various sensing de...

Load Balancing Using Artificial Intelligence for Cloud-Enabled Internet of Everything in Healthcare Domain.

Sensors (Basel, Switzerland)
The emergence of the Internet of Things (IoT) and its subsequent evolution into the Internet of Everything (IoE) is a result of the rapid growth of information and communication technologies (ICT). However, implementing these technologies comes with ...

Control and study of bio-inspired quadrupedal gaits on an underactuated miniature robot.

Bioinspiration & biomimetics
This paper presents a linear quadratic Gaussian (LQG) controller for controlling the gait of a miniature, foldable quadruped robot with individually actuated and controlled legs (MinIAQ-III). The controller is implemented on a palm-size robot made by...

Toward Region-Aware Attention Learning for Scene Graph Generation.

IEEE transactions on neural networks and learning systems
Scene graph generation (SGGen) is a challenging task due to a complex visual context of an image. Intuitively, the human visual system can volitionally focus on attended regions by salient stimuli associated with visual cues. For example, to infer th...

Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm.

Veterinary pathology
Exercise-induced pulmonary hemorrhage (EIPH) is a relevant respiratory disease in sport horses, which can be diagnosed by examination of bronchoalveolar lavage fluid (BALF) cells using the total hemosiderin score (THS). The aim of this study was to e...

Improving energy consumption prediction for residential buildings using Modified Wild Horse Optimization with Deep Learning model.

Chemosphere
The consumption of a significant quantity of energy in buildings has been linked to the emergence of environmental problems that can have unfavourable effects on people. The prediction of energy consumption is widely regarded as an effective method f...