Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection (MIMII) is a sound dataset of industrial machine sounds.
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ToyADMOS dataset is a machine operating sounds dataset of approximately 540 hours of normal machine operating sounds and over 12,000 samples of anomalous sounds collected with four microphones at a 48kHz sampling rate, prepared by Yuma Koizumi and members in NTT Media Intelligence Laboratories. The ToyADMOS dataset is designed for anomaly detection in machine operating sounds (ADMOS) research. It is designed for three tasks of ADMOS: product inspection (toy car), fault diagnosis for fixed machine (toy conveyor), and fault diagnosis for moving machine (toy train).
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Contains normal driving videos together with a set of anomalous actions in its training set. In the test set of the DAD dataset, there are unseen anomalous actions that still need to be winnowed out from normal driving.
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The NINCO (No ImageNet Class Objects) dataset is introduced in the ICML 2023 paper In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation. The images in this dataset are free from objects that belong to any of the 1000 classes of ImageNet-1K (ILSVRC2012), which makes NINCO suitable for evaluating out-of-distribution detection on ImageNet-1K .
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Unconstrained Face Detection and Open-Set Face Recognition Challenge
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