Search results for " Image Processing"
showing 10 items of 2323 documents
Deep learning to detect built cultural heritage from satellite imagery. - Spatial distribution and size of vernacular houses in Sumba, Indonesia -
2021
Abstract In Sumba Island – Indonesia, the implantation of vernacular houses, inside and outside traditional villages, is considered to be an efficient proxy for the on-going complex cultural transformations resulting from globalization. This study presents an easily reproducible workflow allowing buildings to be automatically detected from satellite imagery, demonstrating how modern computer vision methods based on deep learning can help in this task, which would be far too time-consuming when undertaken by hand. Eight deep learning architectures based on convolutional neural networks were compared in terms of ability to identify and locate precisely traditional houses from satellite images…
Demand Sharing Inaccuracies in Supply Chains: A Simulation Study
2018
We investigate two main sources of information inaccuracies (i.e., errors and delays) in demand information sharing along the supply chain (SC). Firstly, we perform a systematic literature review on inaccuracy in demand information sharing and its impact on supply chain dynamics. Secondly, we model several SC settings using system dynamics and assess the impact of such information inaccuracies on SC performance. More specifically, we study the impact of four factors (i.e., demand error, demand delay, demand variability, and average lead times) using three SC dynamic performance indicators (i.e., bullwhip effect, inventory variability, and average inventory). The results suggest that demand …
Refitting Solutions Promoted by $$\ell _{12}$$ Sparse Analysis Regularizations with Block Penalties
2019
International audience; In inverse problems, the use of an l(12) analysis regularizer induces a bias in the estimated solution. We propose a general refitting framework for removing this artifact while keeping information of interest contained in the biased solution. This is done through the use of refitting block penalties that only act on the co-support of the estimation. Based on an analysis of related works in the literature, we propose a new penalty that is well suited for refitting purposes. We also present an efficient algorithmic method to obtain the refitted solution along with the original (biased) solution for any convex refitting block penalty. Experiments illustrate the good be…
Unsupervised Eye Blink Artifact Identification in Electroencephalogram
2018
International audience; The most prominent type of artifact contaminating electroencephalogram (EEG) signals is the eye blink (EB) artifact. Hence, EB artifact detection is one of the most crucial pre-processing step in EEG signal processing before this artifact can be removed. In this work, an approach that identifies EB artifacts without human supervision and automated varying threshold setting is proposed and evaluated. The algorithm functions on the basis of correlation between two EEG electrodes, Fp1 and Fp2, followed by EB artifact threshold determination utilizing the amplitude displacement from the mean. The proposed approach is validated and evaluated in terms of accuracy and error…
Conception d'architectures compactes pour la détection spatiotemporelle d'actions en temps réel
2022
This thesis tackles the spatiotemporal action detection problem from an online, efficient, and real-time processing point of view. In the last decade, the explosive growth of video content has driven a broad range of application demands for automating human action understanding. Aside from accurate detection, vast sensing scenarios in the real-world also mandate incremental, instantaneous processing of scenes under restricted computational budgets. However, current research and related detection frameworks are incapable of simultaneously fulfilling the above criteria. The main challenge lies in their heavy architectural designs and detection pipelines to extract pertinent spatial and tempor…
An ontology for cognitive mimetics
2018
AI and autonomous systems are intended to replace people in several jobs. People have worked in these jobs being able to execute the required information processing. This implies that new technical artefacts must be able to perform equitably effective information processing. Thus, it makes sense to develop the analysis of human information processing in designing intelligent systems. This approach has been termed cognitive mimetics. This paper studies how it would be practical to gain knowledge about human information processing and organize this knowledge using ontologies.
Exploiting deep learning algorithms and satellite image time series for deforestation prediction
2022
In recent years, we have witnessed the emergence of Deep Learning (DL) methods, which have led to enormous progress in various fields such as automotive driving, computer vision, medicine, finances, and remote sensing data analysis. The success of these machine learning methods is due to the ever-increasing availability of large amounts of information and the computational power of computers. In the field of remote sensing, we now have considerable volumes of satellite images thanks to the large number of Earth Observation (EO) satellites orbiting the planet. With the revisit time of satellites over an area becoming shorter and shorter, it will probably soon be possible to obtain daily imag…
Real-time micro-expression analysis by artificial vision
2022
Human-computer interaction technologies focus more and more on the human being, whether it is on his identity, or on his physical and mental state. Significant progress has been made in the last few decades. However, the study of thoughts and emotions is still an underdeveloped field, but one that has begun to gain considerable interest. In this field, the analysis of facial expressions is the preferred treatment.Unlike a macro-expression, which is visible to the eye, a micro-expression is a type of involuntary facial expression that is extremely rapid and of very low intensity. The computer vision scientific community has been studying ways to automatically recognize micro-expressions usin…
Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation
2019
Abstract Recent advances in intrusion detection systems based on machine learning have indeed outperformed other techniques, but struggle with detecting multiple classes of attacks with high accuracy. We propose a method that works in three stages. First, the ExtraTrees classifier is used to select relevant features for each type of attack individually for each (ELM). Then, an ensemble of ELMs is used to detect each type of attack separately. Finally, the results of all ELMs are combined using a softmax layer to refine the results and increase the accuracy further. The intuition behind our system is that multi-class classification is quite difficult compared to binary classification. So, we…
Development of artificial neural network for condition assessment of bridges based on hybrid decision making method – Feasibility study
2021
Abstract Managing a bridge at an appropriate level of reliability requires knowledge of its technical condition, which is decisive in terms of maintenance and repair activities. This is a multi-criteria decision-making problem which results from the need to allocate limited financial resources to this work. Although many calculation models have been suggested in published sources, none of them has ever met these requirements. The algorithm presented by the authors allows for the assessment of any number of bridges, taking into account the diversity of solutions in terms of materials and structures, and can provide a solution to this problem. This hybrid calculation model, combining the modi…