91 citations · 189 across the 5 of their papers we have counts for
6 papers
Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
Elias Kassapis, Georgi Dikov, Deepak K. Gupta +1
In semantic segmentation tasks, input images can often have more than one plausible interpretation, thus allowing for multiple valid labels. To capture such ambiguities, recent wor…
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection
Mohsen Ghafoorian, Cedric Nugteren, Nóra Baka +2
Convolutional neural networks have been successfully applied to semantic segmentation problems. However, there are many problems that are inherently not pixel-wise classification p…
A model-driven approach for a new generation of adaptive libraries
Marco Cianfriglia, Flavio Vella, Cedric Nugteren +2
Efficient high-performance libraries often expose multiple tunable parameters to provide highly optimized routines. These can range from simple loop unroll factors or vector sizes…
CLBlast: A Tuned OpenCL BLAS Library
Cedric Nugteren
This work introduces CLBlast, an open-source BLAS library providing optimized OpenCL routines to accelerate dense linear algebra for a wide variety of devices. It is targeted at ma…
CLTune: A Generic Auto-Tuner for OpenCL Kernels
Cedric Nugteren, Valeriu Codreanu
This work presents CLTune, an auto-tuner for OpenCL kernels. It evaluates and tunes kernel performance of a generic, user-defined search space of possible parameter-value combinati…
PENCIL: Towards a Platform-Neutral Compute Intermediate Language for DSLs
Riyadh Baghdadi, Albert Cohen, Serge Guelton +9
We motivate the design and implementation of a platform-neutral compute intermediate language (PENCIL) for productive and performance-portable accelerator programming.