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 ...
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 ...
Video-Based Anomaly Detection, Urban Surveillance, Scale-Projective Ambiguity, Riemannian Manifold, Scale-Covariant Tracking, ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Jinsong Yu shares deep architectural insights ...
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 ...
Anomaly detection in the context of data science is detecting a data sample that is out of the ordinary and does not fit into the general data pattern (or an outlier). This deviation can result from a ...
Teaching yourself deep learning is a long and arduous process. You need a strong background in linear algebra and calculus, good Python programming skills, and a solid grasp of data science, machine ...
One key part of Microsoft’s big bet on machine learning is that these technologies need to be democratized, turned into relatively simple-to-understand building blocks that Microsoft’s developer ...
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