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Found 5 papers, 5 papers with code
Self-supervised Learning for Sonar Image Classification
Self-supervised learning has proved to be a powerful approach to learn image representations without the need of large labeled datasets.
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent Autoencoders
Ice accumulation in the blades of wind turbines can cause them to describe anomalous rotations or no rotations at all, thus affecting the generation of electricity and power output.
Evaluation of Deep Neural Network Domain Adaptation Techniques for Image Recognition
It has been well proved that deep networks are efficient at extracting features from a given (source) labeled dataset.
Pre-trained Models for Sonar Images
Machine learning and neural networks are now ubiquitous in sonar perception, but it lags behind the computer vision field due to the lack of data and pre-trained models specifically for sonar images.
Speaker Fluency Level Classification Using Machine Learning Techniques
Level assessment for foreign language students is necessary for putting them in the right level group, furthermore, interviewing students is a very time-consuming task, so we propose to automate the evaluation of speaker fluency level by implementing machine learning techniques.
