Complex networks (CNs) have gained much attention in recent years due to their
importance and popularity. The rapid growth in the size of CNs leads to more difficulties in …

In the first days of social networking, the typical view of a community was a set of user
profiles of the same interests and likes, and this community kept enlarging by searching …

Rapid detection and identification of Fusarium germinate spores play a vital role in the early
prediction and effective management of wheat scab disease. This study proposed an …

In this paper, a parallel deep learning-based community detection method in large complex
networks (CNs) is proposed. First, a CN partitioning method is employed to divide the CN …

Detecting communities is an important multidisciplinary research discipline and is
considered vital to understand the structure of complex networks. Deep autoencoders have …

Community detection is a crucial research orientation in complex network owing to its
practical applications. Recently, the convolutional neural network (CNN) based edge …

Alzheimer's disease (AD) is the most common cause of dementia, marked by cognitive
decline and memory loss. Recently, machine learning and deep learning techniques have …

Community detection is one of the long standing and challenging tasks in the field of
Complex Networks (CNs). Recently, deep learning is one of the promising community …

Wheat scab is a highly destructive disease that adversely impact wheat crops throughout
their growth cycle. It is crucial to promptly evaluate the levels of wheat scab in the field to …

For traditional single-passage machine reading comprehension, the text data of a single
passage does not well reflect the complexity of practical application scenarios. Many …