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Concept

Affine shape adaptation

Publications associées (24)

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Olga Fink, Ismail Nejjar, Mengjie Zhao

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these ...

Elsevier2024

Improving Few-Shot Object Detection with Object Part Proposals

Devis Tuia, Marc Conrad Russwurm

Few-Shot Object Detection (FSOD) allows fast adaptation of an object detection model to new classes of objects using few examples per class. This has many applications, in particular in satellite and aerial observation, as it allows learning from experts w ...

The Institute of Electrical and Electronics Engineers, Inc2023

Improving Object Detection under Domain Shifts

Vidit Vidit

Object detection plays a critical role in various computer vision applications, encompassing domains like autonomous vehicles, object tracking, and scene understanding. These applica- tions rely on detectors that generate bounding boxes around known object ...

EPFL2023

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

We present an efficient and accurate people detection approach based on deep learning to detect people attacks and intrusion in video surveillance scenarios Unlike other approaches using background segmentation and pre-processing techniques, which are not ...

2020

Trustworthy Face Recognition: Improving Generalization of Deep Face Presentation Attack Detection

Amir Mohammadi

The extremely high recognition accuracy achieved by modern, convolutional neural network (CNN) based face recognition (FR) systems has contributed significantly to the adoption of such systems in a variety of applications, from mundane activities like unlo ...

EPFL2020

Learning and leveraging shared domain semantics to counteract visual domain shifts

Róger Bermúdez Chacón

One of the main limitations of artificial intelligence today is its inability to adapt to unforeseen circumstances. Machine Learning (ML), due to its data-driven nature, is particularly susceptible to this. ML relies on observations in order to learn impli ...

EPFL2020

Dual Generator Generative Adversarial Networks for Multi-domain Image-to-Image Translation

Yan Yan, Wei Wang

State-of-the-art methods for image-to-image translation with Generative Adversarial Networks (GANs) can learn a mapping from one domain to another domain using unpaired image data. However, these methods require the training of one specific model for every ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Achieving high-resolution thermal imagery in low-contrast lake surface waters by aerial remote sensing and image registration

David Andrew Barry, Ulrich Lemmin, Daniel Sage, Abolfazl Irani Rahaghi

A two-platform measurement system for realizing airborne thermography of the Lake Surface Water Temperature (LSWT) with ~0.8 m pixel resolution (sub-pixel satellite scale) is presented. It consists of a tethered Balloon Launched Imaging and Monitoring Plat ...

2019

On Matching Pursuit and Coordinate Descent

Martin Jaggi, Sebastian Urban Stich, Sai Praneeth Reddy Karimireddy

Two popular examples of first-order optimization methods over linear spaces are coordinate descent and matching pursuit algorithms, with their randomized variants. While the former targets the optimization by moving along coordinates, the latter considers ...

2018

INTRA-CLASS COVARIANCE ADAPTATION IN PLDA BACK-ENDS FOR SPEAKER VERIFICATION

Petr Motlicek, Subhadeep Dey

Multi-session training conditions are becoming increasingly common in recent benchmark datasets for both text-independent and text-dependent speaker verification. In the state-of-the-art i-vector framework for speaker verification, such conditions are addr ...

Ieee2017

Blob properties in full-turbulence simulations of the TCV scrape-off layer

Ivo Furno, Paolo Ricci, Benoît Labit, Fabio Avino, Federico Nespoli, Federico David Halpern, Fabio Riva

To investigate blob properties in the tokamak scrape-off layer (SOL), we perform dedicated numerical nonlinear simulations of plasma turbulence in the SOL of a TCV discharge using the Global Braginskii Solver code. A blob detection technique is used for th ...

2017

Hermite Snakes with Control of Tangents

Michaël Unser, Julien René Fageot, Virginie Sophie Uhlmann

We introduce a new model of parametric contours defined in a continuous fashion. Our curve model relies on Hermite spline interpolation and can easily generate curves with sharp discontinuities; it also grants direct access to the tangent at each location. ...

IEEE2016

Domain Adaptation for Microscopy Imaging

Pascal Fua, Carlos Joaquin Becker, Christos Marios Christoudias

Electron and Light Microscopy imaging can now deliver high-quality image stacks of neural structures. However, the amount of human annotation effort required to analyze them remains a major bottleneck. While Machine Learning algorithms can be used to help ...

Institute of Electrical and Electronics Engineers2015

Steerable PCA for Rotation-Invariant Image Recognition

Michaël Unser, Cédric René Jean Vonesch

In this paper, we propose a continuous-domain version of principal-component analysis, with the constraint that the underlying family of templates appears at arbitrary orientations. We show that the corresponding principal components are steerable. Our met ...

SIAM2015

Non-Linear Domain Adaptation with Boosting

Pascal Fua, Carlos Joaquin Becker, Christos Marios Christoudias

A common assumption in machine vision is that the training and test samples are drawn from the same distribution. However, there are many problems when this assumption is grossly violated, as in bio-medical applications where different acquisitions can gen ...

2013

Quotient-method Algorithms for Input-affine Single-input Nonlinear Systems

Willson Sudarsandhari Shibani

Many real-world systems are intrinsically nonlinear. This thesis proposes various algorithms for designing control laws for input-affine single-input nonlinear systems. These algorithms, which are based on the concept of quotients used in nonlinear control ...

EPFL2012

On Sums of Locally Testable Affine Invariant Properties

Ghid Maatouk

Affine-invariant properties are an abstract class of properties that generalize some central algebraic ones, such as linearity and low-degree-ness, that have been studied extensively in the context of property testing. Affine invariant properties consider ...

Springer2011

Spatio-Chromatic Decorrelation by Shift-Invariant Filtering

Pascal Fua, Sabine Süsstrunk, Matthew Brown

In this paper we derive convolutional filters for colour image whitening and decorrelation. Whilst whitening can be achieved via eigendecomposition of the image patch covariance, this operation is neither efficient nor biologically plausible. Given the shi ...

2011

Learning Real-Time Perspective Patch Rectification

Pascal Fua, Vincent Lepetit

We propose two learning-based methods to patch rectification that are faster and more reliable than state-of-the-art affine region detection methods. Given a reference view of a patch, they can quickly recognize it in new views and accurately estimate the ...

Springer Verlag2011

Single Trial Recognition of Anticipatory Slow Cortical Potentials: The Role of Spatio-Spectral Filtering

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Gangadhar Garipelli

Single trial recognition of slow cortical potentials (SCPs) from full-band EEG (FbEEG) faces different challenges to classical EEG such as noisy, high magnitude (~±100µV) infra slow oscillations (ISO) with f

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011