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Scholarship My journey has been shaped by numerous challenges. I left home at 12 and grew up in the out-of-home care system, which had a significant impact on my academic performance and aspirations. Although I
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In recent years, the rise in cybercrimes has significantly increased the vulnerability of the open internet to various threats and cyber-attacks. Among these, phishing stands out as one of the most perilous crimes worldwide. In a phishing attack, perpetrators create fraudulent websites that...
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals from mobile devices and classify them into different categories or types of ringtones. The...
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Scholar, 2022 Future Leader Alex Wulff The Westpac Scholars Program is more than just a scholarship to me; it is an amazing opportunity to connect and collaborate with a supportive, diverse and inclusive
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biodiversity and sustainability research. The initial objective is to use deep learning techniques to perform acoustic species identification in real-time on low-cost sensing devices coupled to cloud-based
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development process for DL, covering requirement analysis, data collection and labeling, data cleaning, network design, training, testing, and operation. Required knowledge deep learning, natural
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Bachelor of Occupational Therapy (Honours) The Betty Amsden program helped me gain clarity about my career pathway and increase my confidence. I think these were strong contributing factors to excelling in
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. This would provide thousands of diverse example images with corresponding body part locations. These data would be used to train a deep learning model 5, 7 . The model’s high-quality body part predictions may
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that occurs within these biological neural networks, so that these networks can be leveraged for AI applications. In addition, you will develop mathematical and computational neuroscience models
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. Leveraging techniques such as federated learning, differential privacy, and secure multiparty computation, the goal is to enable collaborative ML tasks without compromising the privacy of individual data