Automated machine learning has the ability to improve the efficiency of time series
classification due to the ability to combine multiple feature extraction methods and …

With the continuous occurrence of cybersecurity incidents, network intrusion detection has
become one of the most critical issues in cyber ecosystems. Although previous machine …

The absorption and scattering properties of the water medium cause various types of
distortion in underwater images, which seriously affects the accuracy and effectiveness of …

Infrared ship target segmentation is one of the key technologies for automatically detecting
ship targets in ocean monitoring. However, it is a challenging work to achieve accurate …

In order to spot trends in the methodologies and procedures employed, this systematic
literature review will look at works on time series categorization. Six research questions are …

The continuous rise of inter-contented Internet of Things (IoT) devices has significantly
increased network traffic, complexity, and the ever-changing Internet environment, making …

Time series classification is an essential part of time series analysis research and has
attracted generous researchers' attention. Representation learning and feature space …

Hyperspectral remote sensing technology is becoming increasingly popular in various fields
due to its ability to provide detailed information about crop growth and nutritional status. The …

Deep neural mapping support vector machine (DNMSVM) has achieved good results in
numerous tasks by mapping the input from a low-dimensional space to a high-dimensional …

With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …