2019
AAAI
AAAI 2019
Classifier-Agnostic Saliency Map Extraction
Abstract
Abstract Extracting saliency maps, which indicate parts of the image important to classification, requires many tricks to achieve satisfactory performance when using classifier-dependent methods. Instead, we propose classifier-agnostic saliency map extraction. This allows to find all parts of the image that any classifier could use, not just one given in advance. This way we extract much higher quality saliency maps.
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Conference Pioneer
β AAAI 2019
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Interdisciplinary Bridge
β Artificial Intelligence and Computer Vision and Deep Learning and Machine Learning
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Trend Setter
β Interpretability
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Keyword Pioneer
β saliency map extraction
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Hot Topic Early Bird
β feature attribution
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Cross-Pollinator
β Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio