Zero-Shot Classification enables machines to recognize objects without prior training. It provides a blueprint for understanding each class, like giving a computer a puzzle to solve with clues like habitat, diet, and characteristics. To recognize zebras, we don't need to show the computer countless images.
Jun 12, 2024
Jun 28, 2024 · This classification is a specific type of zero-shot classification applied to visual data. It allows models to classify images into categories they haven't ...
Jun 21, 2024 · Abstract:Zero-shot text learning enables text classifiers to handle unseen classes efficiently, alleviating the need for task-specific training data.
Jun 10, 2024 · Zero-shot means the ability of a machine learning model to classify completely unseen data. What is zero-shot learning in NLP?
Jun 21, 2024 · Multi-label zero-shot learning is a method for classifying images into multiple unseen categories for which no training data is available, while in general zero ...
Jun 20, 2024 · Zero-shot learning allows models to recognize and classify unseen categories by using information from related tasks or external knowledge sources. This ...
Jun 12, 2024 · Zero-Shot Learning (ZSL) is a machine learning paradigm that enables models to classify data into categories they have never encountered during training. . If ...
Jun 17, 2024 · In this paper, we tackle the case of zero-shot classification in the presence of unlabeled data. We leverage the graph structure of the unlabeled data and ...
Jun 23, 2024 · Zero-shot text learning enables text classifiers to handle unseen classes efficiently, alleviating the need for task-specific training data.