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Author/Affiliation: Mi Lu
Extended Buffer-referred Prefetching to Leverage Prefetch Coverage
This paper is an extension of the work originally presented in the 26th International Con- ference on Automation and Computing. This study regarding hardware prefetching aims at concealing cache misses, leading to maximizing the performance of modern processors. This paper leverages prefetch coverage improvement as a way to achieve the goal. Original work proposes two…
Read More Dilated Fully Convolutional Neural Network for Depth Estimation from a Single Image
Depth prediction plays a key role in understanding a 3D scene. Several techniques have been developed throughout the years, among which Convolutional Neural Network has recently achieved state-of-the-art performance on estimating depth from a single image. However, traditional CNNs suffer from the lower resolution and information loss caused by the pooling layers. And oversized parameters…
Read More Advanced Multiple Linear Regression Based Dark Channel Prior Applied on Dehazing Image and Generating Synthetic Haze
Haze removal is an extremely challenging task, and object detection in the hazy environment has recently gained much attention due to the popularity of autonomous driving and traffic surveillance. In this work, the authors propose a multiple linear regression haze removal model based on a widely adopted dehazing algorithm named Dark Channel Prior. Training this…
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