Stock ranking prediction is an effective method for screening high investment value stocks in
the future and can strongly assist investors in making decisions. However, this task is also …

At present, rotating machinery is widely used in all walks of life and has become the key
equipment in many production processes. It is of great significance to strengthen the …

The sudden outbreak of COVID-19 has dramatically altered the state of the global economy,
and the stock market has become more volatile and even fallen sharply as a result of its …

Stock forecasting has always been challenging as the stock market is affected by a
combination of factors. Temporal Convolutional Network (TCN) based on convolutional …

Using machine learning coupled with stock price data to predict stock price trends has
attracted increasing attention from data mining and machine learning communities. An …

Stock price prediction is a classical interdisciplinary issue drawn from finance, computer
science, econometrics, and mathematics. Most stock price data are nonlinear, nonstationary …

Missing data imputation aims to accurately impute the unobserved regions with complete
data in the real world. Although many current methods have made remarkable advances …

Saliency detection is increasingly a crucial task in the computer vision area. In previous
graph-based saliency detection, superpixels are usually regarded as the primary processing …

In the dynamic and uncertain stock market, precise forecasting and decision-making are
crucial for profitability. Traditional deep neural networks (DNN) often struggle with capturing …

Most medical images are low in contrast because adequate details that may prove vital
decisions are not visible to the naked eye. Also, due to the low‐contrast nature of the image …