Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions
The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
artificial intelligence-related technologies. In engineering scenarios, machines usually work …
A review of methods for imbalanced multi-label classification
Abstract Multi-Label Classification (MLC) is an extension of the standard single-label
classification where each data instance is associated with several labels simultaneously …
classification where each data instance is associated with several labels simultaneously …
A comparison of undersampling, oversampling, and SMOTE methods for dealing with imbalanced classification in educational data mining
Educational data mining is capable of producing useful data-driven applications (eg, early
warning systems in schools or the prediction of students' academic achievement) based on …
warning systems in schools or the prediction of students' academic achievement) based on …
A survey on long-tailed visual recognition
L Yang, H Jiang, Q Song, J Guo - International Journal of Computer Vision, 2022 - Springer
The heavy reliance on data is one of the major reasons that currently limit the development
of deep learning. Data quality directly dominates the effect of deep learning models, and the …
of deep learning. Data quality directly dominates the effect of deep learning models, and the …
A systematic review on imbalanced data challenges in machine learning: Applications and solutions
In machine learning, the data imbalance imposes challenges to perform data analytics in
almost all areas of real-world research. The raw primary data often suffers from the skewed …
almost all areas of real-world research. The raw primary data often suffers from the skewed …
Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application
Attention Mechanism has become very popular in the field of mechanical fault diagnosis in
recent years and has become an important technique for scholars to study and apply. The …
recent years and has become an important technique for scholars to study and apply. The …
Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis
Artificial intelligence (AI) systems for computer-aided diagnosis and image-based screening
are being adopted worldwide by medical institutions. In such a context, generating fair and …
are being adopted worldwide by medical institutions. In such a context, generating fair and …
Machine learning-guided protein engineering
Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …
machine learning methods. These methods leverage existing experimental and simulation …
Potential sources of sensor data anomalies for autonomous vehicles: An overview from road vehicle safety perspective
Outstanding steps towards intelligent transportation systems with autonomous vehicles have
been taken in the past few years. Nevertheless, the safety issue in autonomous vehicles is …
been taken in the past few years. Nevertheless, the safety issue in autonomous vehicles is …
A comparative performance analysis of data resampling methods on imbalance medical data
Medical datasets are usually imbalanced, where negative cases severely outnumber
positive cases. Therefore, it is essential to deal with this data skew problem when training …
positive cases. Therefore, it is essential to deal with this data skew problem when training …