Adversarial attacks pose a major challenge in computer vision, where small, nearly imperceptible modifications to input images can mislead classifiers into making incorrect predictions. CODIP ...
Multi-Class Classification Using New PyTorch Best Practices, Part 2: Training, Accuracy, Predictions
Following new best practices, Dr. James McCaffrey of Microsoft Research revisits multi-class classification for when the variable to predict has three or more possible values. This is the second of ...
Dr. James McCaffrey of Microsoft Research: When multi-class data is skewed toward one or more classes, it's very important to analyze accuracy by class. A multi-class classification problem is one ...
Abstract: Fine-grained image classification attempts to accurately classify images that are similar to each other. Multiview information is often used to improve the classification accuracy. Although ...
A constantly evolving document. Calculation of baselines for various datasets used in my NLP research and related projects. No hyperparameter optimization has been carried out to calculate these ...
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