Recent advancements in deep learning architecture have increased its utility in real-life
applications. Deep learning models require a large amount of data to train the model. In …

Credit card fraud is becoming a serious and growing problem as a result of the emergence
of innovative technologies and communication methods, such as contactless payment. In …

Compared to traditional machine learning, deep learning can learn deeper abstract data
representation and understand scattered data properties. It has gained considerable …

Massive usage of credit cards has caused an escalation of fraud. Usage of credit cards has
resulted in the growth of online business advancement and ease of the e-payment system …

In an actual industrial scenario, machines typically operate normally for the majority of the
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …

As technology advanced and e-commerce services expanded, credit cards became one of
the most popular payment methods, resulting in an increase in the volume of banking …

Online transactions, medical services, financial transactions, and banking all have their
share of fraudulent activity. The annual revenue generated by fraud exceeds $1 trillion. Even …

In recent years, machine learning has made great progress in intrusion detection, network
protection, anomaly detection, and other issues in cyberspace. However, these traditional …

Electronic payment methods have become increasingly popular for business transactions,
both online and in-person, across the globe. Anomalies like online fraud and default …

The popularity of the internet, smartphones, and social networks has contributed to the
proliferation of misleading information like fake news and fake reviews on news blogs …