Publications associées à MnO2 nanosheets as an artificial enzyme to mimic oxidase for rapid and sensitive detection of glutathione

Organ-specific biotransformation in salmonids: Insight into intrinsic enzyme activity and biotransformation of three micropollutants

Aquatic ecosystems continue to be threatened by chemical pollution. To what extent organisms are able to cope with chemical exposure depends on their ability to display mechanisms of defense across different organs. Among these mechanisms, biotransformatio ...

Elsevier2024

Detecting Anomalies and Obstacles in Road Scenes

Krzysztof Maciej Lis

We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

EPFL2023

AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES

Lloyd Haydn Hughes

Taking advantage of Capella's ability to dwell on a target for an extended period of time (nominally 30s) in its spotlight (SP) mode, an unsupervised methodology for detecting moving targets in this data is presented in this paper. By colourizing short seg ...

IEEE2023

Reshaping Perception for Autonomous Driving with Semantic Keypoints

Lorenzo Bertoni

The field of artificial intelligence is set to fuel the future of mobility by driving forward the transition from advanced driver-assist systems to fully autonomous vehicles (AV). Yet the current technology, backed by cutting-edge deep learning techniques, ...

EPFL2022

Radatron: Accurate Detection Using Multi-resolution Cascaded MIMO Radar

Waleed Ahmed, Saurabh Gupta, Haitham Al Hassanieh, Junfeng Guan, Seyedsohrab Madani

Millimeter wave (mmWave) radars are becoming a more popular sensing modality in self-driving cars due to their favorable characteristics in adverse weather. Yet, they currently lack sufficient spatial resolution for semantic scene understanding. In this pa ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Improving the Training of Compact Neural Networks for Visual Recognition

Shuxuan Guo

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

EPFL2022

Vision-based Drone Flocking in Outdoor Environments

Dario Floreano, Fabian Maximilian Schilling, Fabrizio Schiano

Decentralized deployment of drone swarms usually relies on inter-agent communication or visual markers that are mounted on the vehicles to simplify their mutual detection. This letter proposes a vision-based detection and tracking algorithm that enables gr ...

2021

Deep Generative Models and Applications

Tatjana Chavdarova

Over the past few years, there have been fundamental breakthroughs in core problems in machine learning, largely driven by advances in deep neural networks. The amount of annotated data drastically increased and supervised deep discriminative models exceed ...

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

Exploring the relative efficacy of motion artefact correction techniques for EEG data acquired during simultaneous fMRI

João Pedro Forjaco Jorge

Simultaneous EEG-fMRI allows multiparametric characterisation of brain function, in principle enabling a more complete understanding of brain responses; unfortunately the hostile MRI environment severely reduces EEG data quality. Simply eliminating data se ...

Wiley2019

Enzyme annotation for orphan and novel reactions using knowledge of substrate reactive sites

Ljubisa Miskovic, Vassily Hatzimanikatis, Noushin Hadadi, Marianne Seijo

Thousands of biochemical reactions with characterized activities are “orphan,” meaning they cannot be assigned to a specific enzyme, leaving gaps in metabolic pathways. Novel reactions predicted by pathway-generation tools also lack associated sequences, l ...

National Academy of Sciences2019

Hardware Implementation of a Smart Camera with Keypoint Detection and Description

Yusuf Leblebici, Selman Ergünay

Feature detection and description constitute important steps of many computer vision applications such as object detection and panorama stitching. Since those steps are computationally heavy, they might occupy significant portion of the full operation. Alt ...

IEEE2018

Mean-Field methods for Structured Deep-Learning in Computer Vision

Pierre Bruno Baqué

In recent years, Machine Learning based Computer Vision techniques made impressive progress. These algorithms proved particularly efficient for image classification or detection of isolated objects. From a probabilistic perspective, these methods can predi ...

EPFL2018

Variational Methods for Human Modeling

Timur Bagautdinov

A large part of computer vision research is devoted to building models and algorithms aimed at understanding human appearance and behaviour from images and videos. Ultimately, we want to build automated systems that are at least as capable as people when i ...

EPFL2018

Target Detection with Deep Learning in Polarimetric Imaging

Yusuf Leblebici, Selman Ergünay, Süha Kagan Köse

Polarimetric imaging techniques demonstrate enhanced capabilities in advanced object detection tasks with their capability to discriminate man-made objects from natural background surfaces. While spectral signatures carry information only about material pr ...

SPIE-INT SOC OPTICAL ENGINEERING2018

Vision-based detection of aircrafts and UAVs

Artem Rozantsev

Unmanned Aerial Vehicles are becoming increasingly popular for a broad variety of tasks ranging from aerial imagery to objects delivery. With the expansion of the areas, where drones can be efficiently used, the collision risk with other flying objects inc ...

EPFL2017

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

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

Object Detection with Active Sample Harvesting

Olivier Canévet

The work presented in this dissertation lies in the domains of image classification, object detection, and machine learning. Whether it is training image classifiers or object detectors, the learning phase consists in finding an optimal boundary between po ...

EPFL2017

Vision-Based Unmanned Aerial Vehicle Detection and Tracking for Sense and Avoid Systems

Denis Gillet, Alcherio Martinoli, Pascal Fua, Vincent Lepetit, Steven Adriaan Roelofsen, Artem Rozantsev, Krishna Raj Sapkota

We propose an approach for on-line detection of small Unmanned Aerial Vehicles (UAVs) and estimation of their relative positions and velocities in the 3D environment from a single moving camera in the context of sense and avoid systems. This problem is cha ...

Ieee2016

Precursor molecule for the synthesis of d-luciferin

Aurélien Godinat, Elena Goun

The present invention relates to precursor molecules for the synthesis of D-luciferin, or blocked D-luciferin and derivatives thereof, which are functionalized in different positions. Further, the use of functionalized precursor molecules for the synthesis ...

2015