An edge detector based on artificial neural network with application to hybrid Compact-WENO finite difference schemes
Related publications (35)
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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 ...
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 ...
"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 ...
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 ...
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 ...
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
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
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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 ...
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 ...
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 ...