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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
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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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Although deep learning has produces state of the art results on many problems, it is a data hungry technology requiring a lot of human supervision in the form of annotated data. Potential PhD topic
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Over the past decades, we have witnessed the emergence and rapid development of deep learning. DL has been successfully deployed in many real-life applications, including face recognition, automatic
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to learn robotics or human-centered research methods will also be considered. Experience with programming languages (particularly Python), deep learning frameworks, and robotic simulation platforms (ROS
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. This is indeed what AIC, BIC, MDL and MML would anticipate. And yet deep learning methods can often work despite this. This project investigates how deep learning can survive over-fitting and whether
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of the AAAI Conference on Artificial Intelligence (Vol. 26, No. 1, pp. 267-273). - Blau, T., Bonilla, E. V., Chades, I., & Dezfouli, A. (2022, June). Optimizing sequential experimental design with deep
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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]). This project investigates methods to enable high performing NMT in low-resource scenarios. [1] Neural Machine Translation for Bilingually Scarce Scenarios: A Deep Multi-task Learning Approach Poorya Zaremoodi
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the WATOC Dirac Medal. As the successful candidate, you will contribute to the design and implementation of AI models that integrate quantum mechanical theory with deep learning, enabling rapid and