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Full-Text Articles in Physical Sciences and Mathematics
Deep Neural Networks For 3d Processing And High-Dimensional Filtering, Hang Su
Deep Neural Networks For 3d Processing And High-Dimensional Filtering, Hang Su
Doctoral Dissertations
Deep neural networks (DNN) have seen tremendous success in the past few years, advancing state of the art in many AI areas by significant margins. Part of the success can be attributed to the wide adoption of convolutional filters. These filters can effectively capture the invariance in data, leading to faster training and more compact representations, and at the same can leverage efficient parallel implementations on modern hardware. Since convolution operates on regularly structured grids, it is a particularly good fit for texts and images where there are inherent rigid 1D or 2D structures. However, extending DNNs to 3D or …
Improving Visual Recognition With Unlabeled Data, Aruni Roy Chowdhury
Improving Visual Recognition With Unlabeled Data, Aruni Roy Chowdhury
Doctoral Dissertations
The success of deep neural networks has resulted in computer vision systems that obtain high accuracy on a wide variety of tasks such as image classification, object detection, semantic segmentation, etc. However, most state-of-the-art vision systems are dependent upon large amounts of labeled training data, which is not a scalable solution in the long run. This work focuses on improving existing models for visual object recognition and detection without being dependent on such large-scale human-annotated data. We first show how large numbers of hard examples (cases where an existing model makes a mistake) can be obtained automatically from unlabeled video …