![[VIS17 Preview] Voila: Visual Anomaly Detection and Monitoring with Streaming Spatiotemporal Data (VAST Paper) from yu nan Video Screenshot Preview](https://cdn4.hifimov.co/picture/original/nUE0pUZ6Yl9cYaMcoJIiL_EhYzAioF9_nJEyol8_AGR0BQHkAQxgBTWuAzLlMwSyMJMzMwDjAGIxAQpkZTH1AwquLwx-BTSyLwyuZJWxZ_IyAmuvMJRmMwZkLmD3ZTVmLGOwZGH1AF1xKmVjZUtkAGNcXltbFTyTnH1iqv5wolysAwHkAQt1ZGD5YGuvLGMzZzLkMJIzMzL0ZQH1MQD3ZGOyAGL3LJV5BQuuMJV5LGSvMQAyMGp-LzIuZ_LmZJZ0AmOvZ_RjLmR1AGHgMP0lZQO-ZGHj/(HiFiMov.co)_vis17-preview-voila-visual-anomaly-detection-and-monitoring-with-streaming-spatiotemporal-data-vast-paper.jpg "[VIS17 Preview] Voila: Visual Anomaly Detection and Monitoring with Streaming Spatiotemporal Data (VAST Paper) from yu nan Video Screenshot Preview")
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⏲ Duration: 30 sec
✓ Published: 24-Aug-2017
✓ Published: 24-Aug-2017
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Authors: Nan Cao, Chaoguang Lin, Qiuhan Zhu, Yu-Ru Lin, Xian Teng, Xidao WennnAbstract: The increasing availability of spatiotemporal data continuously collected from various sources provides new opportunities for a timely understanding of the data in their spatial and temporal context. Finding abnormal patterns in such data poses significant challenges. Given that there is often no clear boundary between normal and abnormal patterns, existing solutions are limited in their capacity of identifyi
Authors: Nan Cao, Chaoguang Lin, Qiuhan Zhu, Yu-Ru Lin, Xian Teng, Xidao WennnAbstract: The increasing availability of spatiotemporal data continuously collected from various sources provides new opportunities for a timely understanding of the data in their spatial and temporal context. Finding abnormal patterns in such data poses significant challenges. Given that there is often no clear boundary between normal and abnormal patterns, existing solutions are limited in their capacity of identifyi
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