Any computer vision application development starts off by acquiring images and data, then
preprocessing and pattern recognition steps to perform a task. When the acquired images …

The existence of class imbalance in a dataset can greatly bias the classifier towards majority
classification. This discrepancy can pose a serious problem for deep learning models, which …

Supervised classification methods have been widely utilized for the quality assurance of the
advanced manufacturing process, such as additive manufacturing (AM) for anomaly …

Planktonic organisms including phyto-, zoo-, and mixoplankton are key components of
aquatic ecosystems and respond quickly to changes in the environment, therefore their …

Learning classifiers with imbalanced data can be strongly biased toward the majority class.
To address this issue, several methods have been proposed using generative adversarial …

Ecological studies of some of the most numerous organisms on the planet, zooplankton,
have been limited by manual analysis for more than 100 years. With the development of …

In part due to its ability to mimic any data distribution, Generative Adversarial Network (GAN)
algorithms have been successfully applied to many applications, such as data …

As one of the most salient features of China's economic development, high-speed rail (HSR)
is considered to be an attractive target and travel mode for terrorists. Distinguishing potential …

Advances in in situ marine life imaging have significantly increased the size and quality of
available datasets, but automatic image analysis has not kept pace. Machine learning has …

Credit risk forecasting generally aims to evaluate the default probability of users in financial
service. It is usually regarded as a binary classification problem, which suffers from the …