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Neurite Tracing in Fluorescence Microscopy Images Using Ridge Filtering and Graph Searching: Principles and Validation

Publications associées (38)

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Attribute Prediction as Multiple Instance Learning

Devis Tuia, Diego Marcos Gonzalez

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

2022

Detection and Measurement of Matrix Discontinuities in UHPFRC by Means of Distributed Fiber Optics Sensing

Bartlomiej Wojciech Sawicki, Antoine Bassil

Following the significant improvement in their properties during the last decade, Distributed Fiber Optics sensing (DFOs) techniques are nowadays implemented for industrial use in the context of Structural Health Monitoring (SHM). While these techniques ha ...

2020

SIPS: Unsupervised Succinct Interest Points

Davide Scaramuzza, Titus Cieslewski

Detecting interest points is a key component of vision-based estimation algorithms, such as visual odometry or visual SLAM. Classically, interest point detection has been done with methods such as Harris, FAST, or DoG. Recently, better detectors have been ...

2018

Sparse Gradient Optimization and its Applications in Image Processing

Nikolaos Arvanitopoulos Darginis

Millions of digital images are captured by imaging devices on a daily basis. The way imaging devices operate follows an integral process from which the information of the original scene needs to be estimated. The estimation is done by inverting the integra ...

EPFL2017

3D-Printed Beam Splitter for Polar Neutral Molecules

Andreas Osterwalder, Sean Dennis Steven Gordon

We describe a macroscopic beam splitter for polar neutral molecules. A complex electrode structure is required for the beam splitter which would be very difficult to produce with traditional manufacturing methods. Instead, we make use of a nascent manufact ...

Amer Physical Soc2017

Automated Reconstruction of Evolving Curvilinear Tree Structures

Przemyslaw Rafal Glowacki

Curvilinear networks are prevalent in nature and span many different scales, ranging from micron-scale neural structures in the brain to petameter-scale dark-matter arbors binding massive galaxy clusters. Reliably reconstructing them in an automated fashio ...

EPFL2016

Localizing Polygonal Objects in Man-Made Environments

Xiaolu Sun

Object detection is a significant challenge in Computer Vision and has received a lot of attention in the field. One such challenge addressed in this thesis is the detection of polygonal objects, which are prevalent in man-made environments. Shape analysis ...

EPFL2015

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

Coupled Structure-from-Motion and 3D Symmetry Detection for Urban Facades

Mark Pauly, Duygu Ceylan

Repeated structures are ubiquitous in urban facades. Such repetitions lead to ambiguity in establishing correspondences across sets of unordered images. A decoupled structure-from-motion reconstruction followed by symmetry detection often produces errors: ...

Association for Computing Machinery2014

Exploiting Scene Cues for Dropped Object Detection

Jean-Marc Odobez, Florent Monay Michaud

This paper presents a method for the automated detection of dropped objects in surveillance scenarios, which is a very important task for abandoned object detection. Our method works in single views and exploits prior information of the scene, such as geom ...

2014