167 estimation-methods "https:" "Computer Vision Center" positions at Monash University
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Deepfakes, derived from "deep learning" and "fake," involve techniques that merge the face images of a target person with a video of a different source person. This process creates videos where the target person appears to be performing actions or speaking as the source person. In a broader...
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of mobile ringtones. Traditional machine learning methods and transformer models will be used to learn patterns from audio signals and classify ringtones into predefined categories (e.g., default ringtones
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Indigenous PhD Scholarship in Artistic research methods for music and science collaboration Job No.: 689424 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term
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-view learning that are robust under distribution shift and missing modalities. The key objectives include: Develop scalable Bayesian deep learning methods for uncertainty estimation in modern neural
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PhD Scholarship - Novel methods to enhance the use of routinely collected linked data for the evaluation of government policies related to healthy ageing Job No.: 691415 Location: Frankston
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Lecturer (Education Focused) - Electrical and Computer Systems Engineering Job No.: 688449 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $118,974
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Lecturer/ Senior Lecturer - Electrical and Computer Systems Engineering Job No.: 688022 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $114,951
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methods, the goal is to enhance the ability to identify and mitigate the risks posed by fraudulent online platforms. Required knowledge Python programming Machine learning background Text analysis Image
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time. In this project, we propose a method for identifying and classifying such emerging asynchronous trends. The goal is to be able to predict how a new emerging trend will develop using similar
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analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images