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Keyphrases
Goat
100%
Machine Learning Models
83%
Dairy Goat
50%
Temporal Observations
50%
Unsupervised Deep Learning
50%
Wireless
50%
Spatiotemporal
50%
Internet-of-animals
50%
Convolutional Neural Network
50%
Animal Health Care
50%
Activity Analysis
50%
Healthcare Monitoring
50%
Data Scarcity
50%
Generalisability
50%
Machine Learning
50%
Class Imbalance
50%
Accelerometer Data
50%
Minority Class
50%
On the Move
50%
Animal Monitoring
33%
Labeled Data
33%
Supraventricular Ectopic Beats
33%
Unseen
33%
Electrocardiogram Classification
33%
Mare
33%
Sampling Rate
33%
Multilayer Perceptron
33%
Orientation Dependence
33%
Hybrid Convolutional Neural Network
33%
Animal Recognition
33%
Input Type
33%
Model Generalization
33%
Artificial Intelligence-driven
33%
Balanced Accuracy
33%
Living Conditions
33%
Deep Learning
33%
Accelerometer
33%
Misclassification
33%
Deep Learning Model
33%
Data Transformation
33%
Goat Industry
16%
Calculation Module
16%
Wireless Accelerometer
16%
Healthy Living
16%
UWB Tag
16%
Goat Farming
16%
Accelerometer Tag
16%
Production Process
16%
Livestock
16%
Activity Data
16%
Milk
16%
Automated Monitoring System
16%
Energy Consumption
16%
General Health
16%
Flanders
16%
Health Problems
16%
Predictive Health Management
16%
Systematic Application
16%
Electrocardiogram
16%
Expert Features
16%
Physiological Events
16%
Series Transformer
16%
Clinical Deployment
16%
Automated Feature Selection
16%
Daily Interactions
16%
Abnormal Heartbeats
16%
Precision Farming Technologies
16%
Resource-limited Areas
16%
High Recognition Accuracy
16%
Targeted Solutions
16%
Digital Health Platform
16%
Interval Features
16%
Real-time Insights
16%
Medical Complexity
16%
Healthcare Scenario
16%
Proactive Monitoring
16%
Proactive Health Management
16%
Ability to Generalize
16%
Animal Behavior
16%
Behavioral Characteristics
16%
Inter-individual Variation
16%
Motivation
16%
Wearable Sensors
16%
Lifesaving
16%
Balanced Performance
16%
Subject-specific
16%
Novel Methodology
16%
Ubiquitous Sensors
16%
Ventricular Arrhythmia
16%
Supervised Learning
16%
Specific Calibration
16%
Putting
16%
Arrhythmia
16%
Modern Healthcare
16%
Data Required
16%
Life-limiting Conditions
16%
Ventricular Ectopic Beats
16%
Electrocardiogram Analysis
16%
Health Outcomes
16%
Systematic Implementation
16%
Second Use
16%
Living Systems
16%
Anomaly Detection System
16%
Learning Difficulties
16%
Dynamic Threshold
16%
Accuracy Class
16%
Clinical Workflow
16%
Real-world Deployment
16%
Weighted Loss Function
16%
Electrocardiogram Signal
16%
Technological Innovation
16%
One-size-fits-all
16%
Dynamic Anomaly
16%
Advanced Deep Learning
16%
Human Annotator
16%
Personalization
16%
Majority Class
16%
Three-axis
16%
Deep Learning Architectures
16%
Learning from Imbalanced Data
16%
Sensor Placement
16%
Cardiologists
16%
Manual Interpretation
16%
Evolving Technologies
16%
Detection Framework
16%
Machine Learning Applications
16%
Individual-specific
16%
Continuous Wavelet Transform
16%
Activity Recognition
16%
Unsupervised Anomaly Detection
16%
Leave-one-out
16%
Performance Metrics
16%
Ethical Regulation
16%
Privacy Regulation
16%
Automated Analysis
16%
Gait Recognition
16%
Feature Selection
16%
Drive System
16%
RR Interval
16%
Technological Synergy
16%
Sensor Noise
16%
Genetic Behavior
16%
Orientation Invariant
16%
High Cost
16%
Health Events
16%
Time Series Data
16%
Equine Gait
16%
Data Representation
16%
Recent Advances
16%
Few-shot
16%
Vector Magnitude
16%
Dual Problem
16%
Timely Intervention
16%
Data Sampling Rate
16%
Health Data
16%
L2 Norm
16%
Trace Class
16%
Biological Characteristics
16%
Overall Accuracy
16%
2-norm
16%
Behavioral Variation
16%
Time-frequency Representation
16%
Accurate Classification
16%
Validation Set
16%
Behavioral Data
16%
Veterinarians
16%
Discrete Fourier Transform
16%
Animal Welfare
16%
Three-axis Accelerometer
16%
Biological Variability
16%
Artificial Intelligence
16%
Complex Data Streams
16%
Comparative Analysis
16%
Gait
16%
Balanced Dataset
16%
Complex Time Series
16%
Systematic Evaluation
16%
Illness
16%
Healthcare
16%
Supervised Machine Learning
16%
Parturition
16%
Training Phase
16%
Loss Function
16%
Farming Operations
16%
Operational Efficiency
16%
Data Analytics
16%
Health Monitoring
16%
False Alarm
16%
Computer Science
Machine Learning Model
100%
Convolutional Neural Network
66%
Class Imbalance
50%
Machine Learning
50%
Artificial Intelligence
50%
Learning System
50%
Sampling Rate
50%
Accelerometer Data
50%
Minority Class
45%
Activity Recognition
41%
Labeled Example
33%
Feature Selection
33%
Efficient Algorithm
33%
Feature Extraction
33%
Use Case
33%
Deep Learning Model
29%
Data Transformation
29%
Deep Learning Method
29%
Multilayer Perceptron
25%
Cross-Validation
25%
Training Phase
16%
Time Series Data
16%
Unsupervised Anomaly Detection
16%
Data Representation
16%
Supervised Learning
16%
Imbalanced Data
16%
Automated Analysis
16%
Data Stream
16%
Setting Research
16%
Majority Class
16%
Performance Metric
16%
Direct Consequence
16%
Gold Standard
16%
Data Processing
16%
Sensor Placement
16%
Conventional Method
16%
Behavioral Data
16%
time-frequency representation
16%
Operational Efficiency
16%
Dual Problem
16%
Behavioral Characteristic
16%
Persistence
16%
Living Condition
12%
Fourier Transform
12%
Validation Set
12%
Comparative Analysis
12%
Classification Accuracy
12%