Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study

CJ Preetha, H Meredig, G Brugnara… - The Lancet Digital …, 2021 - thelancet.com
Background Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue
contrast during MRI scans and play a crucial role in the management of patients with cancer …

Towards secure intrusion detection systems using deep learning techniques: Comprehensive analysis and review

SW Lee, M Mohammadi, S Rashidi… - Journal of Network and …, 2021 - Elsevier
Providing a high-performance Intrusion Detection System (IDS) can be very effective in
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …

Video generative adversarial networks: a review

N Aldausari, A Sowmya, N Marcus… - ACM Computing Surveys …, 2022 - dl.acm.org
With the increasing interest in the content creation field in multiple sectors such as media,
education, and entertainment, there is an increased trend in the papers that use AI …

Imgagn: Imbalanced network embedding via generative adversarial graph networks

L Qu, H Zhu, R Zheng, Y Shi, H Yin - Proceedings of the 27th ACM …, 2021 - dl.acm.org
Imbalanced classification on graphs is ubiquitous yet challenging in many real-world
applications, such as fraudulent node detection. Recently, graph neural networks (GNNs) …

Multiround transfer learning and modified generative adversarial network for lung cancer detection

KT Chui, BB Gupta, RH Jhaveri, HR Chi… - … Journal of Intelligent …, 2023 - Wiley Online Library
Lung cancer has been the leading cause of cancer death for many decades. With the advent
of artificial intelligence, various machine learning models have been proposed for lung …

Deep learning in electron microscopy

JM Ede - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

A review of generative adversarial networks (GANs) and its applications in a wide variety of disciplines: from medical to remote sensing

A Dash, J Ye, G Wang - IEEE Access, 2023 - ieeexplore.ieee.org
We look into Generative Adversarial Network (GAN), its prevalent variants and applications
in a number of sectors. GANs combine two neural networks that compete against one …

Generative partial multi-view clustering with adaptive fusion and cycle consistency

Q Wang, Z Ding, Z Tao, Q Gao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Nowadays, with the rapid development of data collection sources and feature extraction
methods, multi-view data are getting easy to obtain and have received increasing research …

Generative adversarial networks for spatio-temporal data: A survey

N Gao, H Xue, W Shao, S Zhao, KK Qin… - ACM Transactions on …, 2022 - dl.acm.org
Generative Adversarial Networks (GANs) have shown remarkable success in producing
realistic-looking images in the computer vision area. Recently, GAN-based techniques are …

Deep generative adversarial networks for image-to-image translation: A review

A Alotaibi - Symmetry, 2020 - mdpi.com
Many image processing, computer graphics, and computer vision problems can be treated
as image-to-image translation tasks. Such translation entails learning to map one visual …