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Found 8 papers, 0 papers with code
HoughLaneNet: Lane Detection with Deep Hough Transform and Dynamic Convolution
By utilizing the lane features in the Hough parameter space, the network learns dynamic convolution kernel parameters corresponding to each lane, allowing the Dynamic Convolution Module to effectively differentiate between lane features.
DARWIN: A Highly Flexible Platform for Imaging Research in Radiology
Our platform is consists of a radiomics module and a deep learning module.
Defect segmentation: Mapping tunnel lining internal defects with ground penetrating radar data using a convolutional neural network
This research proposes a Ground Penetrating Radar (GPR) data processing method for non-destructive detection of tunnel lining internal defects, called defect segmentation.
Deep Line Art Video Colorization with a Few References
The color transform network takes the target line art images as well as the line art and color images of one or more reference images as input, and generates corresponding target color images.
Fully Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks
This paper proposes a \emph{fully asynchronous} scheme for the policy evaluation problem of distributed reinforcement learning (DisRL) over directed peer-to-peer networks.
A system for generating complex physically accurate sensor images for automotive applications
We describe an open-source simulator that creates sensor irradiance and sensor images of typical automotive scenes in urban settings.
Pixel Level Data Augmentation for Semantic Image Segmentation using Generative Adversarial Networks
Semantic segmentation is one of the basic topics in computer vision, it aims to assign semantic labels to every pixel of an image.
Efficient Algorithm for Privately Releasing Smooth Queries
Outputting the summary runs in time $O(n^{1+\frac{d}{2d+K}})$, and the evaluation algorithm for answering a query runs in time $\tilde O (n^{\frac{d+2+\frac{2d}{K}}{2d+K}} )$.
