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Published in IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), 2014
A categorization of the various technologies used to implement the Internet of Things.
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Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
A study of the depth-of-field of coded aperture lensless cameras.
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Published in IEEE Transactions on Computational Imaging (TCI), 2018
A pipeline (with detailed evaluation) for performing face detection and verification using thin mask-based lensless cameras. A new large and diverse dataset of lensless face images is also provided.
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Published in IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), 2019
A method based on Gauss-Newton optimization for designing IIR filters with near-linear phase responses.
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Published in IEEE/CVF International Conference on Computer Vision (ICCV), 2019
A deep learning method for reconstructing a high-quality image from a mask-based lensless camera capture.
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Published in IEEE International Conference on Multimedia and Expo (ICME), 2020
A proposed design of a privacy-preserving sensor for machine learning tasks built by adding carefully chosen optical and analog components to a conventional imaging sensor.
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Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Using the recurrent neural tangent kernel to perform kernel-based dimensionality reduction on variable-length signals/sequences
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Published in Optica Optics Express, 2021
A method for extending the depth-of-field of large-aperture time-of-flight cameras with the help of a proposed efficient large-aperture time-of-flight simulator.
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Published in European Conference on Computer Vision (ECCV), 2022
A new multi-scale method for implicit neural representations based on residual learning and Laplacian pyramids resulting in high accuracy with very short training times.
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Published in Neural Information Processing Systems (NeurIPS), 2022
Theoretical and empirical evidence showing how increasing the parameters of a regression model increases its vulnerability to membership inference attacks for various data settings.
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Published in AISTATS, 2023
Study of how regularization can lead to larger models having both improved privacy and performance than their smaller counterparts.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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