Publications related to Adversarial machine learning

Quantification of the suitable rooftop area for solar panel installation from overhead imagery using Convolutional Neural Networks

Roberto Castello, Jean-Louis Scartezzini, Alina Ursula Rosa Walch, Shasha Jiang, Riccardo Cadei

The integration of solar technology in the built environment is realized mainly through rooftop-installed panels. In this paper, we leverage state-of-the-art Machine Learning and computer vision techniques applied on overhead images to provide a geo-locali ...

IOP PUBLISHING LTD2021

Efficient Depth-based Deep Learning Methods for Multi-Party Pose Estimation

Angel Noe Martinez Gonzalez

Human detection and pose estimation are essential components for any artificial system responsive to the presence of humans and that react according to human-centered tasks. Robotic systems are typical examples, for which the body pose represents fine grai ...

EPFL2021

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Jean-Philippe Thiran, Guillaume Marc Georges Vray, Devavrat Tomar, Manana Lortkipanidze

Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality m ...

2021

Real-Time Self-Collision Avoidance in Joint Space for Humanoid Robots

Aude Billard, Mikhail Koptev, Nadia Barbara Figueroa Fernandez

In this letter, we propose a real-time self-collision avoidance approach for whole-body humanoid robot control. To achieve this, we learn the feasible regions of control in the humanoid's joint space as smooth self-collision boundary functions. Collision-f ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning

Hubert Girault, Horst Pick, Natalia Gasilova, Andreas Stephan Lesch, Milica Jovic, Tzu-En Lin, Yingdi Zhu

Skin problems are often overlooked due to a lack of robust and patient-friendly monitoring tools. Herein, we report a rapid, noninvasive, and high-throughput analytical chemical methodology, aiming at real-time monitoring of skin conditions and early detec ...

2021

Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective

Tong Zhang

The advances made in predicting visual saliency using deep neural networks come at the expense of collecting large-scale annotated data. However, pixel-wise annotation is labor-intensive and overwhelming. In this paper, we propose to learn saliency predict ...

2021

DeepImageJ: A user-friendly environment to run deep learning models in ImageJ

Michaël Unser, Daniel Sage, Laurène Donati

DeepImageJ offers a user-friendly solution in ImageJ to run trained deep learning models for biomedical image analysis. It includes guiding tools for reliable analyses, contributing to the democratization of deep learning in microscopy. DeepImageJ is a use ...

NATURE PORTFOLIO2021

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based Image Coding

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Learning-based image codecs produce different compression artifacts, when compared to the blocking and blurring degradation introduced by conventional image codecs, such as JPEG, JPEG~2000 and HEIC. In this paper, a crowdsourcing based subjective quality e ...

IEEE2021

Optimizing Latent Space Directions For GAN-based Local Image Editing

Sabine Süsstrunk, Tong Zhang, Ehsan Pajouheshgar

Generative Adversarial Network (GAN) based localized image editing can suffer from ambiguity between semantic attributes. We thus present a novel objective function to evaluate the locality of an image edit. By introducing the supervision from a pre-traine ...

IEEE2021

Square Attack: a query-efficient black-box adversarial attack via random search

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose the Square Attack, a new score-based black-box

l_2

and

l_\infty

adversarial attack that does not rely on local gradient information and thus is not affected by gradient masking. The Square Attack is based on a randomized search scheme where ...

2020

Adversarial machine learning

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Quantification of the suitable rooftop area for solar panel installation from overhead imagery using Convolutional Neural Networks

Efficient Depth-based Deep Learning Methods for Multi-Party Pose Estimation

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Real-Time Self-Collision Avoidance in Joint Space for Humanoid Robots

Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning

Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective

DeepImageJ: A user-friendly environment to run deep learning models in ImageJ

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based Image Coding

Optimizing Latent Space Directions For GAN-based Local Image Editing

Square Attack: a query-efficient black-box adversarial attack via random search

Efficient Depth-based Deep Learning Methods for Multi-Party Pose Estimation

Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective

Quantification of the suitable rooftop area for solar panel installation from overhead imagery using Convolutional Neural Networks

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based Image Coding

Optimizing Latent Space Directions For GAN-based Local Image Editing

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Real-Time Self-Collision Avoidance in Joint Space for Humanoid Robots

Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning

DeepImageJ: A user-friendly environment to run deep learning models in ImageJ

Square Attack: a query-efficient black-box adversarial attack via random search