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An edge detector based on artificial neural network with application to hybrid Compact-WENO finite difference schemes

Related publications (35)

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A geometry-inspired decision-based attack

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Yujia Liu

Deep neural networks have recently achieved tremen-dous success in image classification. Recent studies havehowever shown that they are easily misled into incorrectclassification decisions by adversarial examples. Adver-saries can even craft attacks by que ...

2019

An improved objective metric to predict image quality using deep neural networks

Touradj Ebrahimi, Pinar Akyazi

Objective quality assessment of compressed images is very useful in many applications. In this paper we present an objective quality metric that is better tuned to evaluate the quality of images distorted by compression artifacts. A deep convolutional neur ...

2019

Attribute-Guided Sketch Generation

Yan Yan, Wei Wang, Xinya Chen

Facial attributes are important since they provide a detailed description and determine the visual appearance of human faces. In this paper, we aim at converting a face image to a sketch while simultaneously generating facial attributes. To this end, we pr ...

IEEE2019

Learning to See through Reflections

Sabine Süsstrunk

"Pictures of objects behind a glass are difficult to interpret" "and understand due to the superposition of two real images: a reflection layer and a background layer. Separation of these two layers is challenging due to the ambiguities in as- signing text ...

IEEE2018

Computational Aesthetics and Image Enhancements using Deep Neural Networks

Bin Jin

Imaging devices have become ubiquitous in modern life, and many of us capture an increasing number of images every day. When we choose to share or store some of these images, our primary selection criterion is to choose the most visually pleasing ones. Yet ...

EPFL2018

SparseFool: a few pixels make a big difference

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Apostolos Modas

Deep Neural Networks have achieved extraordinary results on image classification tasks, but have been shown to be vulnerable to attacks with carefully crafted perturbations of the input data. Although most attacks usually change values of many image's pixe ...

2018

Color Representation in Deep Neural Networks

Sabine Süsstrunk, Martin Pierre Engilberge, Edo Collins

Convolutional neural networks are top-performers on image classification tasks. Understanding how they make use of color information in images may be useful for various tasks. In this paper we analyze the representation learned by a popular CNN to detect a ...

2017

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

Object recognition is one of the most important problems in computer vision. However, visual recognition poses many challenges when tried to be reproduced by artificial systems. A main challenge is the problem of variability: objects can appear across huge ...

EPFL2017

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

Sciences et Techniques de l’Ingénieur (STI)2017

Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation

Mathieu Salzmann, Fatemehsadat Saleh

Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently, CNN-based methods have proposed to fine-tune pre-trained networks using im ...

Springer Int Publishing Ag2016