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Water Hyacinth (Eichhornia crassipes) Detection Using Coarse and High Resolution Multispectral Data
Water Chlorophyll a Estimation Using UAV-Based Multispectral Data and Machine Learning
Vibration-based identification of engine valve clearance using a convolutional neural network
Using supervised machine learning algorithms in pavement degradation monitoring
Using Bayesian Networks to Model Competence of Lifeboat Coxswains
UAV Formation Trajectory Planning Algorithms: A Review
UAV-Based Wetland Monitoring: Multispectral and Lidar Fusion with Random Forest Classification
UAI-FI: using artificial intelligence for automatic passenger counting through Wi-Fi and GPS data
Truck industry classification from anonymous mobile sensor data using machine learning
The Machine Learning Method of PIDVCA
The impact of the combination equilibrium of horizontal and sag-vertical curves on safety
Studying the capabilities of the analytical system based on the machine learning method
SPONTANEOUS CATEGORIZATION AND SELF-LEARNING WITH DEEP AUTOENCODER MODELS
SHORT-TERM TRAFFIC STATE ESTIMATION USING BREAKPOINT FLOW CALCULATION AND MACHINE LEARNING METHODS
Sharkeye: Real-Time Autonomous Personal Shark Alerting via Aerial Surveillance
SeeCucumbers: Using Deep Learning and Drone Imagery to Detect Sea Cucumbers on Coral Reef Flats
Review of UAV Obstacle Avoidance Algorithms
Review of Intelligent Algorithms for Autonomous Path Planning of UAVs
Representative truck activity patterns from anonymous mobile sensor data
Reliability of electric vehicle charging infrastructure: A cross-lingual deep learning approach
Reinforcement learning-based autonomous generation technology for product oil tanker loading schemes
Regional Expressway Freight Volume Prediction Algorithm Based on Meteorological Information
Prediction of Fuel Tankering in Aviation Industry with Machine Learning Algorithms
Predicting Subjective Well-being from a Psychological Perspective
PLSAV: Parallel loop searching and verifying for loop closure detection
Optimizing inventory control through a data-driven and model-independent framework
Modelling Ships Main and Auxiliary Engine Powers with Regression-Based Machine Learning Algorithms