30 citations · 32 across the 4 of their papers we have counts for
5 papers
SemifreddoNets: Partially Frozen Neural Networks for Efficient Computer Vision Systems
Leo F Isikdogan, Bhavin V Nayak, Chyuan-Tyng Wu +3
We propose a system comprised of fixed-topology neural networks having partially frozen weights, named SemifreddoNets. SemifreddoNets work as fully-pipelined hardware blocks that a…
A Machine Learning Imaging Core using Separable FIR-IIR Filters
Masayoshi Asama, Leo F. Isikdogan, Sushma Rao +2
We propose fixed-function neural network hardware that is designed to perform pixel-to-pixel image transformations in a highly efficient way. We use a fully trainable, fixed-topolo…
VisionISP: Repurposing the Image Signal Processor for Computer Vision Applications
Chyuan-Tyng Wu, Leo F. Isikdogan, Sushma Rao +5
Traditional image signal processors (ISPs) are primarily designed and optimized to improve the image quality perceived by humans. However, optimal perceptual image quality does not…
Eye Contact Correction using Deep Neural Networks
Leo F. Isikdogan, Timo Gerasimow, Gilad Michael
In a typical video conferencing setup, it is hard to maintain eye contact during a call since it requires looking into the camera rather than the display. We propose an eye contact…
Automatic ISP image quality tuning using non-linear optimization
Jun Nishimura, Timo Gerasimow, Sushma Rao +3
Image Signal Processor (ISP) comprises of various blocks to reconstruct image sensor raw data to final image consumed by human visual system or computer vision applications. Each b…