Publication

Automation of the diagnosis process in the railway system : Detection of defects in concrete sleepers using vision-based machine learning models

Publications associées (141)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

On Actively Teaching the Crowd to Classify

Is it possible to teach workers while crowdsourcing classification tasks? Amongst the challenges: (a) workers have different (unknown) skills, competence, and learning rate to which the teaching must be adapted, (b) feedback on the workers’ progress is lim ...

2013

Learning to Detect Objects with Minimal Supervision

Karim Ali

Many classes of objects can now be successfully detected with statistical machine learning techniques. Faces, cars and pedestrians, have all been detected with low error rates by learning their appearance in a highly generic manner from extensive training ...

EPFL2012

Accurate and Efficient Linear Structure Segmentation by Leveraging Ad Hoc Features with Learned Filters

Vincent Lepetit, Roberto Rigamonti

Extracting linear structures, such as blood vessels or dendrites, from images is crucial in many medical imagery applications, and many handcrafted features have been proposed to solve this problem. However, such features rely on assumptions that are never ...

Springer2012

Learning Separable Filters

Pascal Fua, Vincent Lepetit, Roberto Rigamonti

While learned image features can achieve great accuracy on different Computer Vision problems, their use in real-world situations is still very limited as their extraction is typically time-consuming. We therefore propose a method to learn image features t ...

2012

A Real-Time Deformable Detector

Pascal Fua, François Fleuret, Karim Ali, David Hasler

We propose a new learning strategy for object detection. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform base ...

Institute of Electrical and Electronics Engineers2012

Multiple Object Tracking via Prediction and Filtering with a Sobolev-Type Metric on Curves

Maria Colombo

The problem of multi-target tracking of deforming objects in video sequences arises in many situations in image processing and computer vision. Many algorithms based on finite dimensional particle filters have been proposed. Recently, particle filters for ...

Springer Berlin Heidelberg2012

A Fast Parts-based Approach to Speaker Verification using Boosted Slice Classifiers

Sébastien Marcel, Anindya Roy

Speaker verification on portable devices like smartphones is gradually becoming popular. In this context, two issues need to be considered: 1) such devices have relatively limited computation resources, and 2) they are liable to be used everywhere, possibl ...

2012

A Fast Parts-Based Approach to Speaker Verification Using Boosted Slice Classifiers

Sébastien Marcel, Mathew Magimai Doss, Anindya Roy

Speaker verification (SV) on portable devices like smartphones is gradually becoming popular. In this context, two issues need to be considered: 1) such devices have relatively limited computation resources, and 2) they are liable to be used everywhere, po ...

2012

Tasting Families of Features for Image Classification

François Fleuret, Charles Dubout

Using multiple families of image features is a very efficient strategy to improve performance in object detection or recognition. However, such a strategy induces multiple challenges for machine learning methods, both from a computational and a statistical ...

2011

Comparing machines and humans on a visual categorization test

François Fleuret, Charles Dubout, Ting Li

Automated scene interpretation has benefited from advances in machine learning, and restricted tasks, such as face detection, have been solved with sufficient accuracy for restricted settings. However, the performance of machines in providing rich semantic ...

2011