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    Design and evaluation of a novel convolutional neural network for short-term vehicle multi-traffic prediction 

    Carvalho Grael, Danilo (2019-08-01)
    Short-term vehicle traffic forecasting is about predicting how traffic indicators are going to be in the near future. The main traffic parameters are: traffic volume, traffic speed, and congestion state. In this thesis, ...
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    Using machine learning methods to aid scientists in laboratory environments 

    Coles, Rory (2019-12-01)
    As machine learning gains popularity as a scientific instrument, we look to create methods to implement it as a laboratory tool for researchers. In the first of two projects, we discuss creating a real-time interference ...
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    Deep learning approach to discontinuity-preserving image registration 

    Ng, Eric (2020-05-01)
    Image registration is an indispensable tool in medical image analysis. Traditionally, registration algorithms are aimed at aligning image pairs using regularizers to impose smoothness restrictions on unknown deformation ...
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    Enhanced knowledge distillation by auxiliary classifiers 

    Asadian, Aryan (2021-08-01)
    Deep neural models have shown promising results in various areas, e.g., computer vision and natural language processing, at the cost of high computation and storage resource consumption. These characteristics of deep neural ...
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    Comparative analysis of deep learning and graph cut algorithms for cell image segmentation 

    Reshad, Ghazal (2020-08-01)
    Image segmentation is a commonly used technique in digital image processing with many applications in the area of computer vision and medical image analysis. The goal of image segmentation is to partition an image into ...
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    Group representation learning for group recommendation 

    Sajadi Ghaemmaghami, Sarina (2021-01-01)
    Group recommender systems facilitate group decision making for a set of individuals (e.g., a group of friends, a team, a corporation, etc.). Existing group recommendation methods mostly learn group members' individual ...
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    JoVA-hinge: joint variational autoencoders for personalized recommendation with implicit feedback 

    Askari Firoozjayi, Bahare (2020-12-01)
    Recently, Variational Autoencoders (VAEs) have shown remarkable performance in collaborative filtering (CF) with implicit feedback. These existing recommendation models learn user representations to reconstruct or predict ...

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    AuthorAsadian, Aryan (1)Askari Firoozjayi, Bahare (1)Carvalho Grael, Danilo (1)Coles, Rory (1)Ng, Eric (1)Reshad, Ghazal (1)Sajadi Ghaemmaghami, Sarina (1)Subject
    Deep learning (7)
    Bayesian Modelling (1)Capacity gap (1)Chest CT (1)Congestion detection (1)Convolutional neural networks (1)Estimated travel time (1)Graph cut (1)Group implicit feedback (1)Group recommendation (1)... View MoreDate Issued2020 (3)2019 (2)2021 (2)Has File(s)Yes (7)

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