34 research outputs found

    Toulouse Hyperspectral Data Set: a benchmark data set to assess semi-supervised spectral representation learning and pixel-wise classification techniques

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    Airborne hyperspectral images can be used to map the land cover in large urban areas, thanks to their very high spatial and spectral resolutions on a wide spectral domain. While the spectral dimension of hyperspectral images is highly informative of the chemical composition of the land surface, the use of state-of-the-art machine learning algorithms to map the land cover has been dramatically limited by the availability of training data. To cope with the scarcity of annotations, semi-supervised and self-supervised techniques have lately raised a lot of interest in the community. Yet, the publicly available hyperspectral data sets commonly used to benchmark machine learning models are not totally suited to evaluate their generalization performances due to one or several of the following properties: a limited geographical coverage (which does not reflect the spectral diversity in metropolitan areas), a small number of land cover classes and a lack of appropriate standard train / test splits for semi-supervised and self-supervised learning. Therefore, we release in this paper the Toulouse Hyperspectral Data Set that stands out from other data sets in the above-mentioned respects in order to meet key issues in spectral representation learning and classification over large-scale hyperspectral images with very few labeled pixels. Besides, we discuss and experiment the self-supervised task of Masked Autoencoders and establish a baseline for pixel-wise classification based on a conventional autoencoder combined with a Random Forest classifier achieving 82% overall accuracy and 74% F1 score. The Toulouse Hyperspectral Data Set and our code are publicly available at https://www.toulouse-hyperspectral-data-set.com and https://www.github.com/Romain3Ch216/tlse-experiments, respectively.Comment: 17 pages, 13 figure

    Environmental behaviour of inorganic pollutants present in raw and desalinated French marine sediments

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    International audienceIn the frame of long-term management of contaminated dredged sediments, this paper is centered on determinating the mobility of inorganic contaminants. A methodology derived from waste characterization has been developed and applied to marine sediments from Lazaret bay (Toulon, southern France) to determine the potential mobilization of inorganic pollutants in specific conditions. It consists of mineral and textural analysis combined with leaching tests. This methodology was applied to untreated, 5.8 % organic matter, light sandy silt harbor sediment and to the same sediment after a desalinization treatment. In both untreated and desalinated sediments, the contaminant content was around 26.1, 0.18, 42.5, 34, 31, 35 and 99 mg kg-1 for As, Cd, Cr, Cu, Ni, Pb and Zn, respectively. After 24 hours of time contact between deionized water and sediments, contaminant release of metals was very low (ca. <0.7 total mass %, for all studied elements) due to low solubility of the bearing solid phases (organic matter, carbonates and sulfides), while Mo and B were widely released. After 48 hours, Cd, As, Mo and B release was higher while more significant but no clear differences for other metal appeared

    p3^3VAE: a physics-integrated generative model. Application to the semantic segmentation of optical remote sensing images

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    The combination of machine learning models with physical models is a recent research path to learn robust data representations. In this paper, we introduce p3^3VAE, a generative model that integrates a perfect physical model which partially explains the true underlying factors of variation in the data. To fully leverage our hybrid design, we propose a semi-supervised optimization procedure and an inference scheme that comes along meaningful uncertainty estimates. We apply p3^3VAE to the semantic segmentation of high-resolution hyperspectral remote sensing images. Our experiments on a simulated data set demonstrated the benefits of our hybrid model against conventional machine learning models in terms of extrapolation capabilities and interpretability. In particular, we show that p3^3VAE naturally has high disentanglement capabilities. Our code and data have been made publicly available at https://github.com/Romain3Ch216/p3VAE.Comment: 21 pages, 11 figures, submitted to the International Journal of Computer Visio

    Dynamique des contaminants inorganiques dans les sédiments de dragage (rÎle spécifique de la matiÚre organique naturelle)

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    La gestion au long terme des sĂ©diments de dragage contaminĂ©s soulĂšve le problĂšme du devenir des Ă©lĂ©ments potentiellement toxiques contenus dans ces matrices. Les paramĂštres physicochimiques influencent la spĂ©ciation et la distribution des contaminants sur les diffĂ©rentes phases porteuses organiques ou minĂ©rales, ainsi lors de la gestion Ă  terre des sĂ©diments la modification de facteurs tels que l aĂ©ration, les cycles d humectation/sĂ©chage et l activitĂ© bactĂ©rienne va influencer les paramĂštres physico-chimiques et donc la spĂ©ciation des contaminants. Afin de prĂ©ciser les mĂ©canismes responsables de la mobilitĂ© des Ă©lĂ©ments potentiellement toxiques et d estimer l acceptabilitĂ© environnementale des sĂ©diments de dragage en scĂ©nario de valorisation (p. ex. butte paysagĂšre, remblai ou sous couche routiĂšre), l Ă©tude a Ă©tĂ© axĂ©e sur trois principales Ă©tapes :I Ă©tablir la caractĂ©risation totale des sĂ©diments (granulomĂ©trie, minĂ©ralogie, teneur en eau, composition de la phase solide, composition de l eau interstitielle) et Ă©valuer selon des procĂ©dures normalisĂ©esl influence de facteurs (pH, L/S, tempĂ©rature ) sur la lixiviation des Ă©lĂ©ments et sur les mĂ©canismes gĂ©ochimiques mpliquĂ©s ; II dĂ©velopper un jeu de paramĂštres d entrĂ©e pour le code gĂ©ochimique ORCHESTRA selon des procĂ©dures normalisĂ©es (quantification des phases porteuses les plus rĂ©actives : argiles, carbonates, oxy-hydroxydes de fer ou d aluminium et matiĂšre organique - acide fulviques et humiques) ; III modĂ©liser et prĂ©dire les courbes de solubilitĂ© des Ă©lĂ©ments dĂ©crites lors des tests normalisĂ©s issus de l Ă©tape (i) par l intermĂ©diaire du jeu de paramĂštres d entrĂ©e dĂ©fini dans l Ă©tape II. Les tests de lixiviation et la rĂ©alisation de modĂšles sont des approches complĂ©mentaires, indispensables pour apprĂ©hender et prĂ©ciser les mĂ©canismes contrĂŽlant la mobilitĂ© et la rĂ©tention des Ă©lĂ©ments. Les modĂ©lisations des tests de lixiviation dynamique en colonne sont trĂšs sensibles aux variations des paramĂštres d entrĂ©e, c est pourquoi les modĂšles pour les Ă©lĂ©ments majeurs doivent ĂȘtre le plus adĂ©quats possible. En gĂ©nĂ©ral, les prĂ©dictions pour Al, Ca, Cl, Fe, H2CO3, Mg, Si, SO4, Cu, Cr, MoO4 2- , Pb et Zn ont Ă©tĂ© proches des donnĂ©es expĂ©rimentales, ce qui a indiquĂ© que les processus majoritaires contrĂŽlant la solubilitĂ© des Ă©lĂ©ments ont Ă©tĂ© pris en compte. Par contre, les prĂ©dictions pour Ni et As n ont pas Ă©tĂ© satisfaisantes, montrant que certains processus de rĂ©tention restent encore inconnus et qu ils ne sont pas pris en compte par la base de donnĂ©es MINETEQ2A. Pour mieux dĂ©crire le comportement d'As, il semblerait intĂ©ressant d intĂ©grer, dans le module NiCA-Donan, la complexation potentielle d'As par la MON.The long-term management of contaminated dredged sediments raises the problem of the fate of the potentially toxic element contained in these matrixes. The physico-chemical parameters influence the speciation and distribution of contaminants between organic or inorganic bearing phases, and the terrestrial management of sediment induces the modification of factors such as oxydation, wetting / drying cycles or bacterial activity that will influence the physico-chemical parameters and thus the contaminant speciation. In order to identify the main mechanisms responsible for the mobility ofpotentially toxic elements and to estimate the environmental acceptability of dredged sediment in valuation scenario (as hill landscape, road fill or undercoat), the study was organized following three main steps I characterizing the sediment (particle size, mineralogy, moisture content, solid phase and pore water composition) and evaluating factors (pH, L / S, temperature ...) that control the leaching of elements, according to standardized procedures, II developing a set of input parameters for the geochemical code ORCHESTRA according to standardized procedures (quantification of the most reactive carrier phases : clays, carbonates, oxyhydroxides of iron or aluminum and organic matter - fulvic and humic acid) III modeling and predicting the solubility curves of the elements described in the standardized tests from step (i) using the set of input parameters defined in step (ii). Leaching tests and implementation models are complementary approaches that are necessary to understand the mechanisms controlling the mobility and retention of elements. Modeling of column dynamic leaching tests is very sensitive to changes in input parameters, so the model for the major elements should be as adequate as possible. The obtained predictions for Al, Ca, Cl, Fe, H2CO3, Mg, Si, SO4 2-, Cu, Cr, MoO4 2-, Pb and Zn were close to the experimental data, which indicates that the main processes controlling the solubility of elements were taken into account. The predictions for Ni and As, however, were not satisfactory, showing that some retention processes are still unknown or were not taken into account by the database MINETEQ2A. A better description of As behavior would require to include inAs complexation by the MON in the module Nica-Donan.TOULON-Bibliotheque electronique (830629901) / SudocSudocFranceF

    «La relation de limitation et d’exception dans le français d’aujourd’hui : exceptĂ©, sauf et hormis comme pivots d’une relation algĂ©brique »

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    L’analyse des emplois prĂ©positionnels et des emplois conjonctifs d’ “exceptĂ©â€, de “sauf” et d’ “hormis” permet d’envisager les trois prĂ©positions/conjonctions comme le pivot d’un binĂŽme, comme la plaque tournante d’une structure bipolaire. PlacĂ©es au milieu du binĂŽme, ces prĂ©positions sont forcĂ©es par leur sĂ©mantisme originaire dĂ»ment mĂ©taphorisĂ© de jouer le rĂŽle de marqueurs d’inconsĂ©quence systĂ©matique entre l’élĂ©ment se trouvant Ă  leur gauche et celui qui se trouve Ă  leur droite. L’opposition qui surgit entre les deux Ă©lĂ©ments n’est donc pas une incompatibilitĂ© naturelle, intrinsĂšque, mais extrinsĂšque, induite. Dans la plupart des cas (emplois limitatifs), cette opposition prend la forme d’un rapport entre une « classe » et le « membre (soustrait) de la classe », ou bien entre un « tout » et une « partie » ; dans d’autres (emplois exceptifs), cette opposition se manifeste au contraire comme une attaque de front portĂ©e par un « tout » Ă  un autre « tout ». De plus, l’inconsĂ©quence induite mise en place par la prĂ©position/conjonction paraĂźt, en principe, tout Ă  fait insurmontable. Dans l’assertion « les Ă©cureuils vivent partout, sauf en Australie » (que l’on peut expliciter par « Les Ă©cureuils vivent partout, sauf [qu’ils ne vivent pas] en Australie »), la prĂ©position semble en effet capable d’impliquer le prĂ©dicat principal avec signe inverti, et de bĂątir sur une telle implication une sorte de sous Ă©noncĂ© qui, Ă  la rigueur, est totalement inconsĂ©quent avec celui qui le prĂ©cĂšde (si « les Ă©cureuils ne vivent pas en Australie », le fait qu’ils « vivent partout » est faux). NĂ©anmoins, l’analyse montre qu’alors que certaines de ces oppositions peuvent enfin ĂȘtre dĂ©passĂ©es, d’autres ne le peuvent pas. C’est, respectivement, le cas des relations limitatives et des relations exceptives. La relation limitative, impliquant le rapport « tout » - « partie », permet de rĂ©soudre le conflit dans les termes d’une somme algĂ©brique entre deux sous Ă©noncĂ©s pourvus de diffĂ©rent poids informatif et de signe contraire. Les valeurs numĂ©riques des termes de la somme Ă©tant dĂ©sĂ©quilibrĂ©es, le rĂ©sultat est toujours autre que zĂ©ro. La relation exceptive, au contraire, qui n’implique pas le rapport « tout » - « partie », n’est pas capable de rĂ©soudre le conflit entre deux sous Ă©noncĂ©s pourvus du mĂȘme poids informatif et en mĂȘme temps de signe contraire : les valeurs numĂ©riques des termes de la somme Ă©tant symĂ©triques et Ă©gales, le rĂ©sultat sera toujours Ă©quivalent Ă  zĂ©ro

    Dynamique des contaminants inorganiques dans les sédiments de dragage : rÎle spécifique de la matiÚre organique naturelle

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    The long-term management of contaminated dredged sediments raises the problem of the fate of the potentially toxic element contained in these matrixes. The physico-chemical parameters influence the speciation and distribution of contaminants between organic or inorganic bearing phases, and the terrestrial management of sediment induces the modification of factors such as oxydation, wetting / drying cycles or bacterial activity that will influence the physico-chemical parameters and thus the contaminant speciation. In order to identify the main mechanisms responsible for the mobility ofpotentially toxic elements and to estimate the environmental acceptability of dredged sediment in valuation scenario (as hill landscape, road fill or undercoat), the study was organized following three main steps I characterizing the sediment (particle size, mineralogy, moisture content, solid phase and pore water composition) and evaluating factors (pH, L / S, temperature ...) that control the leaching of elements, according to standardized procedures, II developing a set of input parameters for the geochemical code ORCHESTRA according to standardized procedures (quantification of the most reactive carrier phases : clays, carbonates, oxyhydroxides of iron or aluminum and organic matter - fulvic and humic acid) III modeling and predicting the solubility curves of the elements described in the standardized tests from step (i) using the set of input parameters defined in step (ii). Leaching tests and implementation models are complementary approaches that are necessary to understand the mechanisms controlling the mobility and retention of elements. Modeling of column dynamic leaching tests is very sensitive to changes in input parameters, so the model for the major elements should be as adequate as possible. The obtained predictions for Al, Ca, Cl, Fe, H2CO3, Mg, Si, SO4 2-, Cu, Cr, MoO4 2-, Pb and Zn were close to the experimental data, which indicates that the main processes controlling the solubility of elements were taken into account. The predictions for Ni and As, however, were not satisfactory, showing that some retention processes are still unknown or were not taken into account by the database MINETEQ2A. A better description of As behavior would require to include inAs complexation by the MON in the module Nica-Donan.La gestion au long terme des sĂ©diments de dragage contaminĂ©s soulĂšve le problĂšme du devenir des Ă©lĂ©ments potentiellement toxiques contenus dans ces matrices. Les paramĂštres physicochimiques influencent la spĂ©ciation et la distribution des contaminants sur les diffĂ©rentes phases porteuses organiques ou minĂ©rales, ainsi lors de la gestion Ă  terre des sĂ©diments la modification de facteurs tels que l’aĂ©ration, les cycles d’humectation/sĂ©chage et l’activitĂ© bactĂ©rienne va influencer les paramĂštres physico-chimiques et donc la spĂ©ciation des contaminants. Afin de prĂ©ciser les mĂ©canismes responsables de la mobilitĂ© des Ă©lĂ©ments potentiellement toxiques et d’estimer l’acceptabilitĂ© environnementale des sĂ©diments de dragage en scĂ©nario de valorisation (p. ex. butte paysagĂšre, remblai ou sous couche routiĂšre), l’étude a Ă©tĂ© axĂ©e sur trois principales Ă©tapes :I Ă©tablir la caractĂ©risation totale des sĂ©diments (granulomĂ©trie, minĂ©ralogie, teneur en eau, composition de la phase solide, composition de l’eau interstitielle) et Ă©valuer selon des procĂ©dures normalisĂ©esl’influence de facteurs (pH, L/S, tempĂ©rature
) sur la lixiviation des Ă©lĂ©ments et sur les mĂ©canismes gĂ©ochimiques mpliquĂ©s ; II dĂ©velopper un jeu de paramĂštres d’entrĂ©e pour le code gĂ©ochimique ORCHESTRA selon des procĂ©dures normalisĂ©es (quantification des phases porteuses les plus rĂ©actives : argiles, carbonates, oxy-hydroxydes de fer ou d’aluminium et matiĂšre organique - acide fulviques et humiques) ; III modĂ©liser et prĂ©dire les courbes de solubilitĂ© des Ă©lĂ©ments dĂ©crites lors des tests normalisĂ©s issus de l’étape (i) par l’intermĂ©diaire du jeu de paramĂštres d’entrĂ©e dĂ©fini dans l’étape II. Les tests de lixiviation et la rĂ©alisation de modĂšles sont des approches complĂ©mentaires, indispensables pour apprĂ©hender et prĂ©ciser les mĂ©canismes contrĂŽlant la mobilitĂ© et la rĂ©tention des Ă©lĂ©ments. Les modĂ©lisations des tests de lixiviation dynamique en colonne sont trĂšs sensibles aux variations des paramĂštres d’entrĂ©e, c’est pourquoi les modĂšles pour les Ă©lĂ©ments majeurs doivent ĂȘtre le plus adĂ©quats possible. En gĂ©nĂ©ral, les prĂ©dictions pour Al, Ca, Cl, Fe, H2CO3, Mg, Si, SO4, Cu, Cr, MoO4 2- , Pb et Zn ont Ă©tĂ© proches des donnĂ©es expĂ©rimentales, ce qui a indiquĂ© que les processus majoritaires contrĂŽlant la solubilitĂ© des Ă©lĂ©ments ont Ă©tĂ© pris en compte. Par contre, les prĂ©dictions pour Ni et As n’ont pas Ă©tĂ© satisfaisantes, montrant que certains processus de rĂ©tention restent encore inconnus et qu’ils ne sont pas pris en compte par la base de donnĂ©es MINETEQ2A. Pour mieux dĂ©crire le comportement d'As, il semblerait intĂ©ressant d’intĂ©grer, dans le module NiCA-Donan, la complexation potentielle d'As par la MON

    Dynamics of inorganic contaminants in dredged sediments : specific role of natural organic matter

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    La gestion au long terme des sĂ©diments de dragage contaminĂ©s soulĂšve le problĂšme du devenir des Ă©lĂ©ments potentiellement toxiques contenus dans ces matrices. Les paramĂštres physicochimiques influencent la spĂ©ciation et la distribution des contaminants sur les diffĂ©rentes phases porteuses organiques ou minĂ©rales, ainsi lors de la gestion Ă  terre des sĂ©diments la modification de facteurs tels que l’aĂ©ration, les cycles d’humectation/sĂ©chage et l’activitĂ© bactĂ©rienne va influencer les paramĂštres physico-chimiques et donc la spĂ©ciation des contaminants. Afin de prĂ©ciser les mĂ©canismes responsables de la mobilitĂ© des Ă©lĂ©ments potentiellement toxiques et d’estimer l’acceptabilitĂ© environnementale des sĂ©diments de dragage en scĂ©nario de valorisation (p. ex. butte paysagĂšre, remblai ou sous couche routiĂšre), l’étude a Ă©tĂ© axĂ©e sur trois principales Ă©tapes :I Ă©tablir la caractĂ©risation totale des sĂ©diments (granulomĂ©trie, minĂ©ralogie, teneur en eau, composition de la phase solide, composition de l’eau interstitielle) et Ă©valuer selon des procĂ©dures normalisĂ©esl’influence de facteurs (pH, L/S, tempĂ©rature
) sur la lixiviation des Ă©lĂ©ments et sur les mĂ©canismes gĂ©ochimiques mpliquĂ©s ; II dĂ©velopper un jeu de paramĂštres d’entrĂ©e pour le code gĂ©ochimique ORCHESTRA selon des procĂ©dures normalisĂ©es (quantification des phases porteuses les plus rĂ©actives : argiles, carbonates, oxy-hydroxydes de fer ou d’aluminium et matiĂšre organique - acide fulviques et humiques) ; III modĂ©liser et prĂ©dire les courbes de solubilitĂ© des Ă©lĂ©ments dĂ©crites lors des tests normalisĂ©s issus de l’étape (i) par l’intermĂ©diaire du jeu de paramĂštres d’entrĂ©e dĂ©fini dans l’étape II. Les tests de lixiviation et la rĂ©alisation de modĂšles sont des approches complĂ©mentaires, indispensables pour apprĂ©hender et prĂ©ciser les mĂ©canismes contrĂŽlant la mobilitĂ© et la rĂ©tention des Ă©lĂ©ments. Les modĂ©lisations des tests de lixiviation dynamique en colonne sont trĂšs sensibles aux variations des paramĂštres d’entrĂ©e, c’est pourquoi les modĂšles pour les Ă©lĂ©ments majeurs doivent ĂȘtre le plus adĂ©quats possible. En gĂ©nĂ©ral, les prĂ©dictions pour Al, Ca, Cl, Fe, H2CO3, Mg, Si, SO4, Cu, Cr, MoO4 2- , Pb et Zn ont Ă©tĂ© proches des donnĂ©es expĂ©rimentales, ce qui a indiquĂ© que les processus majoritaires contrĂŽlant la solubilitĂ© des Ă©lĂ©ments ont Ă©tĂ© pris en compte. Par contre, les prĂ©dictions pour Ni et As n’ont pas Ă©tĂ© satisfaisantes, montrant que certains processus de rĂ©tention restent encore inconnus et qu’ils ne sont pas pris en compte par la base de donnĂ©es MINETEQ2A. Pour mieux dĂ©crire le comportement d'As, il semblerait intĂ©ressant d’intĂ©grer, dans le module NiCA-Donan, la complexation potentielle d'As par la MON.The long-term management of contaminated dredged sediments raises the problem of the fate of the potentially toxic element contained in these matrixes. The physico-chemical parameters influence the speciation and distribution of contaminants between organic or inorganic bearing phases, and the terrestrial management of sediment induces the modification of factors such as oxydation, wetting / drying cycles or bacterial activity that will influence the physico-chemical parameters and thus the contaminant speciation. In order to identify the main mechanisms responsible for the mobility ofpotentially toxic elements and to estimate the environmental acceptability of dredged sediment in valuation scenario (as hill landscape, road fill or undercoat), the study was organized following three main steps I characterizing the sediment (particle size, mineralogy, moisture content, solid phase and pore water composition) and evaluating factors (pH, L / S, temperature ...) that control the leaching of elements, according to standardized procedures, II developing a set of input parameters for the geochemical code ORCHESTRA according to standardized procedures (quantification of the most reactive carrier phases : clays, carbonates, oxyhydroxides of iron or aluminum and organic matter - fulvic and humic acid) III modeling and predicting the solubility curves of the elements described in the standardized tests from step (i) using the set of input parameters defined in step (ii). Leaching tests and implementation models are complementary approaches that are necessary to understand the mechanisms controlling the mobility and retention of elements. Modeling of column dynamic leaching tests is very sensitive to changes in input parameters, so the model for the major elements should be as adequate as possible. The obtained predictions for Al, Ca, Cl, Fe, H2CO3, Mg, Si, SO4 2-, Cu, Cr, MoO4 2-, Pb and Zn were close to the experimental data, which indicates that the main processes controlling the solubility of elements were taken into account. The predictions for Ni and As, however, were not satisfactory, showing that some retention processes are still unknown or were not taken into account by the database MINETEQ2A. A better description of As behavior would require to include inAs complexation by the MON in the module Nica-Donan

    Selective extraction of PAHs from a sediment with structural preservation of Natural Organic Matter

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    International audienceSelective extraction of Polycyclic Aromatic Hydrocarbons (PAH) without structural modification of the Natural Organic Matter (NOM) from a heavily contaminated sediment was investigated using various solvents mixtures. Structural modification of the NOM was monitored after extraction using 3D-fluorescence spectroscopy. Better results were obtained with a 15-h PAH extraction under reflux with a dichloromethane/cyclohexane 20/80 mixture. The experimental procedure was validated with NOM standard materials before to be applied on natural sediments. It could be applied to any environmental solid sample such as sediments and soils

    fMRI functional connectivity estimators robust to region size bias

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    International audienceAnalysis of interactions in the brain in terms of functional resting-state networks has yielded fundamental results in neuroscience. The ïŹrst step in such analyses of functional connectivity typically involves computing correlations between brain regions. In this paper, we show theoretical results explaining why brain region sizes bias correlation estimators, and propose three new estimators to correct for region size in- ïŹ‚uence. We show experimental results on both synthetic and real fMRI data and discuss the inïŹ‚uence of noise and intra-regional correlation on the robustness of the estimators. The bootstrap-based estimator of correlations emerges as the preferred choice
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