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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.
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Project Background & Motivation Active learning (AL) mitigates the heavy annotation costs of deep learning by strategically querying the most informative unlabeled samples. However, traditional AL
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from mobile devices and classify them into different categories or types of ringtones. The activities of the project include gathering a diverse dataset of audio samples representing various types
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best configuration of chart parameters, such as sample size, sampling interval, and control limits, to minimize detection time for process shifts while controlling false alarm rates. It explores both
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In recent years, social media have become a common plattforms for criminals to stalk, intimidate, manipulate and abuse vulnerable citizens, such as women and youth. A recent survey of students in
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The Opportunity Join the Faculty of Engineering as a Technical Officer to support the Student Analytical Makerspace and Pilot Laboratories (SAMPL) and Monash Innovation Labs (MiLabs). The Technical Officer is
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, including managing established processes, preparing Front of House exhibition access and communication plans, maintaining databases, recording attendance, developing surveys and generating reports. Further
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. Working under the guidance of the Professor of the area, the role helps coordinate codesign activities, develop bespoke materials and surveys, and assist with data collection, analysis, and research
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to apply for Monash Jobs '. Please include 2 writing samples in your application: one short form (announcements, social media posts) one long form (a news article, a significant blog post, brochures etc
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similar fragmentation patterns. There is a critical need for generative frameworks that can learn from limited data by intelligently querying the most informative samples, and that can fuse multiple views