As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …

In the past years, deep neural networks (DNN) have become popular in many disciplines
such as computer vision (CV), natural language processing (NLP), etc. The evolution of …

Due to the rapid growth in artificial intelligence (AI) and deep learning (DL) approaches, the
security and robustness of the deployed algorithms need to be guaranteed. The security …

In recent years, significant progress has been achieved using deep neural networks (DNNs)
in obtaining human-level performance on various long-standing tasks. With the increased …

Deep learning approaches have demonstrated great achievements in the field of computer-
aided medical image analysis, improving the precision of diagnosis across a range of …

Purpose The growing application of deep learning in radiology has raised concerns about
cybersecurity, particularly in relation to adversarial attacks. This study aims to systematically …

Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …

Lung cancer remains one of the leading causes of morbidity and mortality worldwide,
making early diagnosis critical for improving therapeutic outcomes and patient prognosis …

Lung cancer is one of the malignant tumor diseases with the fastest increase in morbidity
and mortality, which poses a great threat to human health. Low-Dose Computed …

Recent studies have found that medical images are vulnerable to adversarial attacks.
However, it is difficult to protect medical imaging systems from adversarial examples in that …