Anomaly detection in images is rapidly emerging as a critical field in both industrial quality control and medical diagnostics. Leveraging deep learning techniques, researchers have developed methods ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Ramya Krishnamoorthy shares a detailed case ...

Researchers review the recent advances of deep learning-basedimage anomaly detection since the rapid development ofdeep learning can bring the capabilities of image anomaly detection into the factory ...

Imagimob AI, a development platform for building tinyML applications for edge devices, adds support for deep learning anomaly detection. Deep anomaly detection—the identification of rare items, events ...

In a world that's growing more digital and interconnected by the day, fraud has taken on new dimensions, often dealing crippling blows to business. From online transactions to sensitive data ...

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...

Data from New Zealand’s National Climate Network are operationally verified both during data ingest and post data ingestion into the National Climate Database. The quality control process in the ...

Kinil Doshi is a Senior VP at Citibank and a fintech expert in banking compliance and risk management with two decades of experience. In this article, I want to explore AI applications in fraud ...

In his recent research, technology thought leader Lakshminarayana Reddy has introduced a state-of-the-art blueprint for addressing the ever-increasing risk of credit card fraud. The objective of his ...