Deep learning modelling techniques: current progress, applications, advantages, and challenges
Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
[HTML][HTML] Financial fraud: a review of anomaly detection techniques and recent advances
With the rise of technology and the continued economic growth evident in modern society,
acts of fraud have become much more prevalent in the financial industry, costing institutions …
acts of fraud have become much more prevalent in the financial industry, costing institutions …
Machine learning and deep learning
Today, intelligent systems that offer artificial intelligence capabilities often rely on machine
learning. Machine learning describes the capacity of systems to learn from problem-specific …
learning. Machine learning describes the capacity of systems to learn from problem-specific …
Machine learning for anomaly detection: A systematic review
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …
components from data. Many techniques have been used to detect anomalies. One of the …
Explaining anomalies detected by autoencoders using Shapley Additive Explanations
Deep learning algorithms for anomaly detection, such as autoencoders, point out the
outliers, saving experts the time-consuming task of examining normal cases in order to find …
outliers, saving experts the time-consuming task of examining normal cases in order to find …
Deep learning for anomaly detection: A survey
R Chalapathy, S Chawla - arXiv preprint arXiv:1901.03407, 2019 - arxiv.org
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …
research areas and application domains. The aim of this survey is two-fold, firstly we present …
Deep learning for financial applications: A survey
Computational intelligence in finance has been a very popular topic for both academia and
financial industry in the last few decades. Numerous studies have been published resulting …
financial industry in the last few decades. Numerous studies have been published resulting …
Progress in outlier detection techniques: A survey
Detecting outliers is a significant problem that has been studied in various research and
application areas. Researchers continue to design robust schemes to provide solutions to …
application areas. Researchers continue to design robust schemes to provide solutions to …
Financial cybercrime: A comprehensive survey of deep learning approaches to tackle the evolving financial crime landscape
J Nicholls, A Kuppa, NA Le-Khac - Ieee Access, 2021 - ieeexplore.ieee.org
Machine Learning and Deep Learning methods are widely adopted across financial
domains to support trading activities, mobile banking, payments, and making customer credit …
domains to support trading activities, mobile banking, payments, and making customer credit …
Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …