no code implementations • 19 Nov 2021 • Kamil Oster, Stefan Güttel, Lu Chen, Jonathan L. Shapiro, Megan Jobson
Firstly, it is important to enhance the quality of both sets of data (laboratory measurements and physical sensors) in a data pre-processing stage (as described in Methodology section).
no code implementations • 17 Jun 2021 • Kamil Oster, Stefan Güttel, Jonathan L. Shapiro, Lu Chen, Megan Jobson
In this case, we used principal component analysis (PCA) with Hotelling's $T^2$ statistics to identify the long-term outliers.
no code implementations • 3 Jul 2020 • Amelia Elizabeth Pollard, Jonathan L. Shapiro
Visual Question Answering(VQA) is a highly complex problem set, relying on many sub-problems to produce reasonable answers.
no code implementations • 3 Jul 2020 • Amelia Elizabeth Pollard, Jonathan L. Shapiro
We create and exhibit a new toy dataset, based on the MNIST dataset, which we call MNIST-QA, for testing Visual Question Answering architectures in a low-dimensional environment while preserving the more difficult components of the Visual Question Answering task, and demonstrate the proposed network architecture on this new dataset, as well as on COCO-QA and DAQUAR-FULL.