Veysi Adin

Inference Time,Artificial Neural Network,Long Short-term Memory,Machine Learning Models,Acoustic Emission,Acoustic Emission Signals,Activation Function,Artificial Neural Network Model,Audio Recordings,Concrete Material,Convolutional Neural Network,Convolutional Neural Network Model,Embedded System,Energy Consumption,Feeding Behavior,Hidden Layer,Instantaneous Amplitude,Jaw Movements,Learning Algorithms,Machine Learning,Mode Of Action,Multilayer Perceptron,Power Consumption,Sleep Mode,Structural Health Monitoring,Support Vector Machine,Types Of Damage,Wrong Classification,Accuracy Of Model,Acoustic Sensors,Acoustic Signals,Action Recognition,Algorithmic Approach,Analog-to-digital Converter,Animal Welfare,Attitude Behavior,Audio Data,Audio Input,Autonomous Operation,Balanced Accuracy,Batch Normalization Layer,Berg Balance Scale,Best-performing Model,Bouts Of Activity,Classification Performance,Clock Frequency,Complex Models,Computational Requirements,Convolutional Layers,Damage Identification,