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Milad Rafiee - IEEE Xplore Author Profile
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Milad Rafiee

Publications
3
Citations
46
Publications by Year
20212024
Co-Authors:
Show All Co-Authors (8)
Image of author Milad Rafiee

Milad Rafiee

Affiliation

Department of Informatics
University of Oslo
Oslo, Norway

Publication Topics

Biography

Milad Rafiee is currently a Lecturer and a Research Assistant with the Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran. His research interests include computer networks, the IoT, software-defined networking, parallel and distributed computing, and GPU programming.(Based on document published on 7 December 2020).
Publications
3
Citations
46
Publications by Year
20212024
Co-Authors:
Show All Co-Authors (8)
Author's Published Works

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Change Detection: Discerning Real Changes from Noise on Planetscope Pairs of Images

Sébastien Drouyer

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
Year: 2022 | Conference Paper |
Change detection on satellite image series is a much more complex problem than detecting changes in color or illumination. First, it is subject to common problems inherent to image series: images are generally not well aligned, changes in atmospheric conditions impact the colors and overall contrast of images, and clouds can partially or totally obstruct the areas of interest. Secondly, noise in s...Show More

Change Detection: Discerning Real Changes from Noise on Planetscope Pairs of Images

Sébastien Drouyer

Year: 2022 | Conference Paper |

Out-Of-Distribution As A Target Class in Semi-Supervised Learning

Antoine Tadros;Sébastien Drouyer;Rafael Grompone von Gioi

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
A key limitation of supervised learning is the ability to handle data from unknown distributions. Often, such methods fail when presented with samples from a source not represented in the training data. This work proposes an effective way of controlling the behavior of a neural network in the presence of out-of-distribution examples. For this, the training dataset is supplemented with extraneous d...Show More

Out-Of-Distribution As A Target Class in Semi-Supervised Learning

Antoine Tadros;Sébastien Drouyer;Rafael Grompone von Gioi

Year: 2022 | Conference Paper |

A Review on Contrastive Learning Methods and Applications to Roof-Type Classification on Aerial Images

Ahmed Ben Saad;Sebastien Drouyer;Bastien Hell;Sylvain Gavoille;Stéphane Gaiffas;Gabriele Facciolo

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
Year: 2021 | Conference Paper |
Cited by: Papers (1)
Unsupervised learning based on Contrastive Learning (CL) has attracted a lot of interest recently. This is due to excellent results on a variety of subsequent tasks (especially classification) on benchmark datasets (ImageNet, CIFAR-10, etc.) without the need of large quantities of labeled samples. This work explores the application of some of the most relevant CL techniques on a large unlabeled da...Show More

A Review on Contrastive Learning Methods and Applications to Roof-Type Classification on Aerial Images

Ahmed Ben Saad;Sebastien Drouyer;Bastien Hell;Sylvain Gavoille;Stéphane Gaiffas;Gabriele Facciolo

Year: 2021 | Conference Paper |

Wind Turbine Detection on Sentinel-2 Images

N. Mandroux;T. Dagobert;S. Drouyer;R. Grompone Von Gioi

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
Year: 2021 | Conference Paper |
Cited by: Papers (4)
ESA's Sentinel- 2 satellites have been in orbit for five years, acquiring huge amounts of data all over the world. They are a formidable tool for mass detection as they are freely available. Given their importance in the energetic transition and their spread over countries or continents, wind turbines are natural candidates for such studies. We propose an automatic wind turbine detector for low re...Show More

Wind Turbine Detection on Sentinel-2 Images

N. Mandroux;T. Dagobert;S. Drouyer;R. Grompone Von Gioi

Year: 2021 | Conference Paper |

Oil Depot Detection via CNN Semantic Segmentation

Antoine Tadros;Sébastien Drouyer;Rafael Grompone von Gioi

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
Year: 2021 | Conference Paper |
Neural network methods are nowadays used for a wide variety of tasks, in particular in computer vision. Among those tasks, semantic segmentation aims at labeling every pixel in an image, giving a good understanding of the scene. In this paper, we propose to use two neural network architectures designed for semantic segmentation to detect oil tank depots in Sentinel-2 images. We compare the methods...Show More

Oil Depot Detection via CNN Semantic Segmentation

Antoine Tadros;Sébastien Drouyer;Rafael Grompone von Gioi

Year: 2021 | Conference Paper |

A Contrario Oil Tank Detection with Patch Match Completion

Antoine Tadros;Sébastien Drouyer;Rafael Grompone von Gioi

2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
Year: 2021 | Conference Paper |
Cited by: Papers (2)
The energy sector is a key industry in the global economy and monitoring oil storage provides valuable insights into the economic state of a country. Our aim is to detect oil tank farms as accurately as possible using Sentinel-2 images. An a contrario clustering method is used to group by density the result of a circle detection step. Then, a patch-match procedure is used to complete the tank dete...Show More

A Contrario Oil Tank Detection with Patch Match Completion

Antoine Tadros;Sébastien Drouyer;Rafael Grompone von Gioi

Year: 2021 | Conference Paper |

VehSat: a Large-Scale Dataset for Vehicle Detection in Satellite Images

Sébastien Drouyer

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
Year: 2020 | Conference Paper |
Cited by: Papers (7)
There has been this last decade a major improvement in earth observation imagery, both in terms of resolution and revisit rate. This technological leap comes with an increasing demand for detecting objects in satellite images. In this context, vehicle detection generates a great deal of interest in the scientific and industrial community. Indeed, detecting vehicles can have a range of applications...Show More

VehSat: a Large-Scale Dataset for Vehicle Detection in Satellite Images

Sébastien Drouyer

Year: 2020 | Conference Paper |

Parking Occupancy Estimation on Planetscope Satellite Images

Sébastien Drouyer

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
Year: 2020 | Conference Paper |
Cited by: Papers (3)
This paper presents a method for estimating the occupancy ratio of parkings lots from satellite images. The algorithm takes as input a series of PlanetScope images along with a mask indicating where the parking is positioned and returns for each image an occupancy ratio. The method is generic, doesn't require any calibration and can easily be extended. For validating our results, we have created a...Show More

Parking Occupancy Estimation on Planetscope Satellite Images

Sébastien Drouyer

Year: 2020 | Conference Paper |

Oil Tank Detection in Satellite Images via a Contrario Clustering

Antoine Tadros;Sébastien Drouyer;Rafael Grompone von Gioi;Lucas Carvalho

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
Year: 2020 | Conference Paper |
Cited by: Papers (4)
Monitoring oil stocks provides valuable insights on the balance between production and demand of petroleum products. The identification of oil depots is important for estimating storage capacities and measuring oil stocks. To achieve this purpose, we present an oil tank detector. As oil tanks are generally circular, we use as a first step a circle detection algorithm. However, this approach tends ...Show More

Oil Tank Detection in Satellite Images via a Contrario Clustering

Antoine Tadros;Sébastien Drouyer;Rafael Grompone von Gioi;Lucas Carvalho

Year: 2020 | Conference Paper |

Highway Traffic Monitoring on Medium Resolution Satellite Images

Sébastien Drouyer;Carlo de Franchis

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
Year: 2019 | Conference Paper |
Cited by: Papers (5)
These last years, earth observation imagery has significantly improved. Public satellites such as WorldView-3 can now produce images with a Ground Sample Distance of 31cm, reaching a resolution equivalent to aerial images. Perhaps more importantly, the revisit frequency has also been greatly enhanced: providers such as Planet can now acquire images of a given ground location on a daily basis. Thes...Show More

Highway Traffic Monitoring on Medium Resolution Satellite Images

Sébastien Drouyer;Carlo de Franchis

Year: 2019 | Conference Paper |

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