Search Results for author: Patrick Hansen

Found 4 papers, 1 papers with code

Fast and Accurate: Video Enhancement using Sparse Depth

no code implementations15 Mar 2021 Yu Feng, Patrick Hansen, Paul N. Whatmough, Guoyu Lu, Yuhao Zhu

This paper presents a general framework to build fast and accurate algorithms for video enhancement tasks such as super-resolution, deblurring, and denoising.

Deblurring Denoising +4

ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems

no code implementations18 Nov 2019 Patrick Hansen, Alexey Vilkin, Yury Khrustalev, James Imber, David Hanwell, Matthew Mattina, Paul N. Whatmough

In this work, we investigate the efficacy of the ISP in CNN classification tasks, and outline the system-level trade-offs between prediction accuracy and computational cost.

FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning

1 code implementation27 Feb 2019 Paul N. Whatmough, Chuteng Zhou, Patrick Hansen, Shreyas Kolala Venkataramanaiah, Jae-sun Seo, Matthew Mattina

Over a suite of six datasets we trained models via transfer learning with an accuracy loss of $<1\%$ resulting in up to 11. 2 TOPS/W - nearly $2 \times$ more efficient than a conventional programmable CNN accelerator of the same area.

General Classification Image Classification +1

Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning

no code implementations4 Dec 2018 Paul Whatmough, Chuteng Zhou, Patrick Hansen, Matthew Mattina

On-device CNN inference for real-time computer vision applications can result in computational demands that far exceed the energy budgets of mobile devices.

Image Classification Transfer Learning

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