Moslem Ouled Sghaier

Moslem Ouled Sghaier
Université de Montréal | UdeM · Center for Mathematical Research

Scientific developer chez OODA Technologies

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19
Publications
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204
Citations

Publications

Publications (19)
Conference Paper
Automatic Identification System (AIS) allows the ships to broadcast important kinematic and static information, and is one of the most commonly used tools for ship traffic monitoring as individual tracks can be inferred from chronological sequence of the ships' AIS messages. In this paper, we propose two deep learning based methods for AIS data ass...
Conference Paper
Full-text available
When it comes to disaster management and mitigation, remote sensing data is considered as one of the most valuable sources of information due to its ability to quickly access to the affected area and all-weather, day and night imaging capability. However, considering the long revisit time of most optical and radar sensors orbiting the Earth, multi-...
Conference Paper
Full-text available
Using information quality attributes to characterize and measure the information quality is necessary to ensure the successful soft and hard data fusion outcome, especially when fusing data of often poor quality such as most of open source data. This paper presents a set of deep learning natural language processing methods for extracting informatio...
Conference Paper
Monitoring flood extent by means of Synthetic Aperture Radar (SAR) images has become a very common practice among decision makers and planners in disaster management as these images provide wide area coverage in extreme weather conditions. However, due to the satellite revisit time, their availability hinders their efficient use in disaster managem...
Conference Paper
Water is an indispensable natural resource for life. Despite the fact that 72% of the Earth's surface is covered with water, only 3% of these water reserves are in the form of fresh water, 96% of which constitutes ice-poles. As a result, countries such as Canada with nearly 9% of the world's renewable water resources may be considered a freshwater-...
Article
Full-text available
Nowadays, satellite images are considered as one of the most relevant sources of information in the context of major disasters management. Their availability in extreme weather conditions and their ability to cover wide geographic areas make them an indispensable tool toward an effective disaster response. Among the various available sensors, Synth...
Conference Paper
Floods rank among the most devastating and deadly disasters likely to occur. Each year, thousands of people die as a result of rising river water levels and spring snow melts. Minimizing the impact of these events and providing necessary information to rescue teams on the ground requires the mobilization of all humanitarian stakeholders. This work...
Conference Paper
The evaluation of lines of communication status in normal times or during crises is a very important task for many applications, such as disaster management and road network maintenance. However, due to their large geographic extent, the inspection of the these structures surfaces using traditional techniques such as laser scanning poses a very cha...
Thesis
Full-text available
Durant les dernières décennies, le domaine de la télédétection et de l’imagerie satellitaire a connu un intérêt accru auprès de plusieurs gouvernements et organisations nationales et internationales. Cet intérêt apparaît dans le nombre énorme de satellites de télédétection qui gravitent autour de la Terre. Les capteurs installés sur ces satellites...
Article
Full-text available
Water bodies extraction using satellite images is of great importance due to its utility in several applications such as land use planning, floods management and monitoring. Among the wide range of sensors orbiting the Earth, Synthetic Aperture Radar (SAR) is a very effective tool in this context due to its robustness in the face of unfavorable wea...
Conference Paper
Water surface extraction using satellite images proves to be of great importance due to its utility in several applications such as land use, floods management and monitoring. Among the wide range of sensors orbiting around the earth, Synthetic Aperture Radar (SAR) proves to be a very effective tool in this context due to its robustness to unfavora...
Conference Paper
Infrastructures damage detection in case of major disasters is one of the most discussed problems and represent an active field of research in remotely sensed imaging. In this paper, a novel method designed for fast roads damage extraction is proposed since these structures are important in the delivery of assistance and to manage the intervention...
Conference Paper
Full-text available
This paper addresses the problem of change detection from very high resolution remotely sensed images and its application on road damage extraction in case of major disaster. The proposed methodology is based on the multiscale image segmentation using the Haar wavelet in order to define the appropriate unit of analysis for the comparison step. The...
Article
Full-text available
Road extraction from very high resolution sensors is a very popular topic in panchromatic and multispectral remote sensing image analysis. Despite the vast number of methods proposed in the literature to deal with this problem, in practice, most are quite limited and do not account for geometric and radiometric variability. Our aim is to propose a...
Conference Paper
Full-text available
Road extraction is a topical research because of complexity due to his large topological variability. Increasing the spatial resolution generates noise which makes extraction difficult, especially in case of major disaster in an urban context. This problem increases false alarm rates and generally affects the performance of road extraction algorith...
Conference Paper
Full-text available
In this paper, a new method for road extraction from very high resolution satellite images is introduced. The proposed methodology is based on multiscale analysis of the image through beamlet transform that can approximate edges of an image by means of line segments appearing at different resolution scales. The hypothesis of the membership of these...
Article
Full-text available
With the increase in resolution of remote sensing image, road extraction nowadays is done with most precision including a better identification of the various road networks. However, this precision comes with a cost. The precision generates noise due to the sensor and the urban context which makes the extraction difficult. This problem increases...
Conference Paper
Full-text available
This paper presents a new approach for automatic building detection in very high resolution satellite images. The proposed method is a cooperative multi-agent approach between both an edge and region approach. In the pretreatment step, a supervisor agent finds a building's corner using Harris detector. Starting from these points, a cooperation proc...

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Projects (2)
Project
Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate most everything in language: web search, advertisement, emails, customer service, language translation, radiology reports, etc. There are a large variety of underlying tasks and machine learning models behind NLP applications. Recently, deep learning approaches have obtained very high performance across many different NLP tasks. These can solve tasks with single end-to-end models and do not require traditional, task-specific feature engineering. This work aims at developing new techniques for NLP understanding based on new deep learing methods and exploring its application in Maritime Domain Awareness (MDA).
Project
Evaluation of image preprocessing operations to allow automatic road detection from radar satellite images. The project focuses on evaluating best filters to reduce radar speckle noise, extract road segments from the image and recombining them to detect a complete road network. This projet aimed at identifying damaged roads to establish a suitable route for rescue teams to navigate to specific locations following a major natural disaster such as earthquakes or flooding.