DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detection

Visual anomaly detection, an important problem in computer vision, is usually formulated as a one-class classification and segmentation task. The student-teacher (S-T) framework has proved to be effective in solving this challenge. However, previous works based on S-T only empirically applied constraints on normal data and fused multi-level information. In this study, we propose an …

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Technical Controls, Rollout, and Edge Cases (Passwordless Authentication Series, #2)

(Editor’s Note: This is the second post in the Passwordless Authentication Series, which shares insights from our journey on enforcing FIDO2 authentication via hardware authenticators (YubiKeys) across all of Palantir. While Palantir has enforced mandatory strong multi-factor authentication for well over a decade, hardware-backed authentication using FIDO2 represents the strongest form of modern authentication available.) …

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Illustrative notebooks in Amazon SageMaker JumpStart

Amazon SageMaker JumpStart is the Machine Learning (ML) hub of SageMaker providing pre-trained, publicly available models for a wide range of problem types to help you get started with machine learning. JumpStart also offers example notebooks that use Amazon SageMaker features like spot instance training and experiments over a large variety of model types and …

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Interactive data prep widget for notebooks powered by Amazon SageMaker Data Wrangler

According to a 2020 survey of data scientists conducted by Anaconda, data preparation is one of the critical steps in machine learning (ML) and data analytics workflows, and often very time consuming for data scientists. Data scientists spend about 66% of their time on data preparation and analysis tasks, including loading (19%), cleaning (26%), and …