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Optimal Classification of Minerals by Microscopic Image Analysis Based on Seven-State “Deep Learning” Combined with Optimizers

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Open Journal of Applied Sciences 2024年第6期14卷 1550-1572页

作者： Kouadio Krah Sie Ouattara Gbele Ouattara alain clement Joseph Vangah Laboratoire de Gnie Civil Gosciences et Sciences Gographiques Institut National Polytechnique Houphout Boigny (INPHB) Yamoussoukro Cte dIvoire Institut National Polytechnique Houphout Boigny (INPHB) Ecole Doctorale Polytechnique (EDP) Yamoussoukro Cte dIvoire Laboratoire des Sciences et Technologies de la Communication et de lInformation (LSTCI) Institut National Polytechnique Houphout Boigny (INP-HB) Yamoussoukro Cte dIvoire Ecole de Gomatique et du Territoire (EGT) Abidjan Cte dIvoire LARIS SFR MATHSTIC Universit dAngers Angers France Universit Virtuelle de Cte dIvoire Abidjan Cte dIvoire

The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, medicine, surveillance or security, agriculture, etc.). Most related works use open source consistent image databases. This is the case for ImageNet reference data such as coco data, IP102, CIFAR-10, STL-10 and many others with variability representatives. The consistency of its images contributes to the spectacular results observed in its fields with deep learning. The application of deep learning which is making its debut in geology does not, to our knowledge, include a database of microscopic images of thin sections of open source rock minerals. In this paper, we evaluate three optimizers under the AlexNet architecture to check whether our acquired mineral images have object features or patterns that are clear and distinct to be extracted by a neural network. These are thin sections of magmatic rocks (biotite and 2-mica granite, granodiorite, simple granite, dolerite, charnokite and gabbros, etc.) which served as support. We use two hyper-parameters: the number of epochs to perform complete rounds on the entire data set and the “learning rate” to indicate how quickly the weights in the network will be modified during optimization. Using Transfer Learning, the three (3) optimizers all based on the gradient descent methods of Stochastic Momentum Gradient Descent (sgdm), Root Mean Square Propagation (RMSprop) algorithm and Adaptive Estimation of moment (Adam) achieved better performance. The recorded results indicate that the Momentum optimizer achieved the best scores respectively of 96.2% with a learning step set to 10−3 for a fixed choice of 350 epochs during this variation and 96, 7% over 300 epochs for the same value of the learning step. This performance is expected to provide excellent insight into image quality for future studies. Then they participate in the development of

关键词： Classification Convolutional Neural Network Deep Learning Optimizers Transfer Learning Rock Mineral Images

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Optimal Classification of Minerals by Microscopic Image Analysis Based on Seven-State “Deep Learning” Combined with Optimizers

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Open Journal of Applied Sciences（应用科学） 2024年第6期 1550页

作者： Kouadio Krah Sie Ouattara Gbele Ouattara alain clement Joseph Vangah

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Optimal Flame Detection of Fires in Videos Based on Deep Learning and the Use of Various Optimizers

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Open Journal of Applied Sciences 2021年第11期11卷 1240-1255页

作者： Tidiane Fofana Sié Ouattara alain clement Laboratoire des Sciences et Technologies de la Communication et de l’Information (LSTCI) Yamoussoukro C&#244te d’Ivoire Institut National Polytechnique Houphouët Boigny (INPHB) Yamoussoukro C&#244te d’Ivoire Ecole Supérieure des Technologies de l’Information et de la Communication (ESATIC) Abidjan C&#244te d’Ivoire LARIS SFR MATHSTIC Université d’Angers Angers France

Deep learning has recently attracted a lot of attention with the aim of developing a fast, automatic and accurate system for image identification and classification. In this work, the focus was on transfer learning and evaluation of state-of-the-art VGG16 and 19 deep convolutional neural networks for fire image classification from fire images. In this study, five different approaches (Adagrad, Adam, AdaMax, Nadam and Rmsprop) based on the gradient descent methods used in parameter updating were studied. By selecting specific learning rates, training image base proportions, number of recursion (epochs), the advantages and disadvantages of each approach are compared with each other in order to achieve the minimum cost function. The results of the comparison are presented in the tables. In our experiment, Adam optimizers with the VGG16 architecture with 300 and 500 epochs tend to steadily improve their accuracy with increasing number of epochs without deteriorating performance. The optimizers were evaluated on the basis of their AUC of the ROC curve. It achieves a test accuracy of 96%, which puts it ahead of other architectures.

关键词： Image Classification Optimizers Transfer Learning VGG16 VGG19

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A New Electronic Instrumentation Approach for the Acquisition of Microscopic Blood Smear Images for the Automatic Diagnosis of Anemia

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Advances in Bioscience and Biotechnology 2020年第6期11卷 237-255页

作者： Jerome Nango Alico Sié Ouattara alain clement Laboratoire des Sciences et Technologies de la Communication et de l’Information (LSTCI) Yamoussoukro Cote D’Ivoire Institut National Polytechnique Houphouet Boigny (INPHB) Yamoussoukro Cote D’Ivoire Institut Universitaire de Technologie d’Angers (IUT) Angers France

Anemia is a blood abnormality that affects the quantity and quality of red blood cells in the human body. This sometimes banal sign spares no continent and no social stratum. This anomaly is generally appreciated through biological analyzes of patients’ blood. These analyzes, which boil down to the knowledge of hemato-metric constants, cannot by themselves allow the characterization of certain forms of anemia in the sense that most anemia are related to the morphology and color of red blood cells. Our work in this paper is to perform blood smears on patients and perform a morphological and colorimetric analysis of red blood cells on these smears. This approach allowed us to highlight on each erythrocyte morphological and colorimetric descriptors to accurately identify the types of anemia by image processing methods. This identification is performed in an automated environment to allow pathologists to respond quickly to anemia-related emergencies and also improve the treatment to be conducted. This automation required the implementation of a new approach to electronic instrumentation and the acquisition of microscopic blood smear images for the automatic and rapid diagnosis of anemia.

关键词： Anemia Instrumentation Acquisition Automated Blood Smears Red Blood Cells Morphological Descriptors Colorimetric Descriptors Image Processing Diagnosis

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A Semi-Vectorial Hybrid Morphological Segmentation of Multicomponent Images Based on Multithreshold Analysis of Multidimensional Compact Histogram

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Open Journal of Applied Sciences 2017年第11期7卷 597-610页

作者： Adles Kouassi Sié Ouattara Jean-Claude Okaingni Wognin J. Vangah alain clement Laboratory of Signals and Electrical Systems (L2SE) Institut National Polytechnique Houphou&euml t Boigny Yamoussoukro C&ocirc te d’Ivoire Institut National Polytechnique Houphouë t Boigny (INPHB) Yamoussoukro C&ocirc te d’Ivoire Ecole Supérieure des Technologies de l’Information et de la Communication (ESATIC) Abidjan C&ocirc te d’Ivoire Institut Universitaire de Technologie d’Angers (IUT) Angers France

In this work, we propose an original approach of semi-vectorial hybrid morphological segmentation for multicomponent images or multidimensional data by analyzing compact multidimensional histograms based on different orders. Its principle consists first of segment marginally each component of the multicomponent image into different numbers of classes fixed at K. The segmentation of each component of the image uses a scalar segmentation strategy by histogram analysis;we mainly count the methods by searching for peaks or modes of the histogram and those based on a multi-thresholding of the histogram. It is the latter that we have used in this paper, it relies particularly on the multi-thresholding method of OTSU. Then, in the case where i) each component of the image admits exactly K classes, K vector thresholds are constructed by an optimal pairing of which each component of the vector thresholds are those resulting from the marginal segmentations. In addition, the multidimensional compact histogram of the multicomponent image is computed and the attribute tuples or ‘colors’ of the histogram are ordered relative to the threshold vectors to produce (K + 1) intervals in the partial order giving rise to a segmentation of the multidimensional histogram into K classes. The remaining colors of the histogram are assigned to the closest class relative to their center of gravity. ii) In the contrary case, a vectorial spatial matching between the classes of the scalar components of the image is produced to obtain an over-segmentation, then an interclass fusion is performed to obtain a maximum of K classes. Indeed, the relevance of our segmentation method has been highlighted in relation to other methods, such as K-means, using unsupervised and supervised quantitative segmentation evaluation criteria. So the robustness of our method relatively to noise has been tested.

关键词： Morphological Segmentation Vectorial Orders Semi-Vectorial Segmentation Multidimensional Compact Histogram Multi-Thresholds Fusion Inter-Class Classification

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A Semi-Vectorial Morphological Segmentation Multi-Component Images of Coumarins on Thin Layer Combined with Laser for Better Separation

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Open Journal of Applied Sciences 2022年第6期12卷 1054-1068页

作者： Theodore Guié Toa Bi Marcelin Sandjé Régnima G. Oscar Sie Ouattara alain clement UFR Science and Technology University of Man Man Ivory Coast Laboratory of Communication and Information Science and Technology (LSTCI) National Polytechnic Institute Houphou&#235 t Boigny Yamoussoukro C&ocirc te d’Ivoire University Institute of Technology of Angers (IUT) Angers France

In this work, we propose an approach for the separation of coumarins from thin-layer morphological segmentation based on the acquisition of multicomponent images integrating different types of coumarins. The first step is to make a segmentation by region, by thresholding, by contour, etc. of each component of the digital image. Then, we proceeded to the calculations of parameters of the regions such as the color standard deviation, the color entropy, the average color of the pixels, the eccentricity from an algorithm on the matlab software. The mean color values atR = 91.20 in red, atB = 213.21 in blue showed the presence of samidin in the extract. The color entropy values HG = 5.25 in green and HB = 4.04 in blue also show the presence of visnadine in the leaves of Desmodium adscendens. These values are used to consolidate the database of separation and discrimination of the types of coumarins. The relevance of our coumarin separation or coumarin recognition method has been highlighted compared to other methods, such as the one based on the calculation of frontal ratios which cannot discriminate between two coumarins having the same frontal ratio. The robustness of our method is proven with respect to the separation and identification of some coumarins, in particular samidin and anglicine.

关键词： Identification Thin Layer Secondary Metabolites Coumarins Image Acquisition Segmentation Standard Deviation Entropy Average Color Algorithm Matlab

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Image Acquisition and Parameter Calculations for Optimization of the Automatic Identification of Terpenes in a Combined Laser Thin Film Extract

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Advances in Materials Physics and Chemistry 2022年第6期12卷 141-154页

作者： Theodore Guié Toa Bi Wognin Vangah Alico Nango Jérôme Sié Ouattara alain clement UFR Science and Technology University of Man Man Ivory Coast Laboratory of Communication and Information Science and Technology (LSTCI) National Polytechnic Institute Houphou&euml t Boigny Yamoussoukro C&ocirc te d’Ivoire University Institute of Technology of Angers (IUT) Angers France

In this work, we propose an original approach to the thin-layer identification of secondary metabolites (terpenes) based on the acquisition of multicomponent images integrating terpenes to be identified. Its principle consists initially of segmentation by region of each component of the image based on the attribute tuples or colors of each region of the digital image. Then we proceeded to the calculations of region parameters such as standard deviation, entropy, average pixel color, eccentricity from an algorithm on the matlab software. These values allowed us to build a database. Finally, we built an algorithm for identifying secondary metabolites (terpenes) on the basis of these data. The relevance of our method of identifying or recognizing terpenes has been demonstrated compared to other methods, such as the one based on the calculation of frontal ratios which cannot discriminate between two terpenes having the same frontal ratio. The robustness of our method with respect to the identification of linalool, limonene was tested.

关键词： Thin Film Terpenes Segmentation Entropy

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Application of the Dempster-Shafer Theory to the Classification of Pixels from Aster Satellite Images and Spectral Indices

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Journal of Applied Mathematics and Physics 2017年第7期5卷 1462-1477页

作者： Jean-Claude Okaingni Sié Ouattara Adles Francis Kouassi Adama Koné Wognin Joseph Vangah alain clement Laboratory of Signals and Electrical Systems (L2SE)) Institut National Polytechnique Houphou&eumlt Boigny Yamoussoukro Cote D’Ivoire Institut National Polytechnique Houphouët Boigny (INPHB) Yamoussoukro Cote D’Ivoire Ecole Supérieure des Technologies de l’Information et de la Communication (ESATIC) Abidjan Cote D’Ivoire Institut Universitaire de Technologie d’Angers (IUT) Angers France

In this paper, it is proposed to apply the Dempster-Shafer Theory (DST) or the theory of evidence to map vegetation, aquatic and mineral surfaces with a view to detecting potential areas of observation of outcrops of geological formations (rocks, breastplates, regolith, etc.). The proposed approach consists in aggregating information by using the DST. From pretreated Aster satellite images (geo-referencing, geometric correction and resampling at 15 m), new channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI. Then, the DST formalism was modeled and generated under the MATLAB software, an image segmented into six classes including three absolute classes (E,V,M) and three classes of confusion ({E,V}, {M,V}, {E,M}). The control on the land, based on geographic coordinates of pixels of different classes on said image, has made it possible to make a concordant interpretation thereof. Our contribution lies in taking into account imperfections (inaccuracies and uncertainties) related to source information by using mass functions based on a simple support model (two focal elements: the discernment framework and the potential set of belonging of the pixel to be classified) with a normal law for the good management of these.

关键词： Dempster-Shafer Theory Belief Functions Source Modeling Aster Satellite Images Spectral Indices Classification

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Design and Performance of a Controlled Environment Mini-chamber for Measuring Produce Quality Deterioration

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Journal of Agricultural Science and Technology(B) 2012年第4期2卷 391-399页

作者： Denyse I. LeBlanc clement Vigneault Jereme Boutin Vicky Toussaint Denis Charlebois Charles F.Fomey Gaetan Bourgeois alain clement Greg S. Bezanson Agriculture and Agri-Food Canada c/o Food Research Centre Universitd de Moncton 18 Antonine-Maillet Ave. Moncton NBE1A 3E9 Canada Agriculture and Agri-Food Canada Horticulture Research and Development Centre 430 Gouin Blvd Saint-Jean-sur-RichelieuQC J3B 3E6 Canada Agriculture and Agri-Food Canada Atlantic Food and Horticulture Research Centre 32 Main St. Kentville NS B4N IJS Canada Agricultureand Agri-Food Canada Food Research and Development Centre 3600 Casavant Bird West St-Hyacinthe QC J2S8E3 Canada

To minimize losses between harvest and retail display, a system is needed to track temperature and RH exposure of fresh produce and predict its quality at each step of the distribution chain. With accurate models, such system could （1） identify problematic situations before losses occur; （2） become a management tool for decision makers; and （3） help quantify the real impact of individual inappropriate conditions. A project was initiated to develop models required for such a decision system. Because the data required to develop models were not available for most fruit and vegetables, a series of storage trials was planned for measuring changes in physiological and microbial quality, and development of physiological disorders and/or diseases, as a function of time, temperature and RH. To meet this objective, controlled environment mini-chambers were designed, built and instrumented for measuring the effect of traceable environmental conditions encountered during storage and transportation of fresh horticultural produce of similar size and shape as tomato. Detailed design and performance evaluation of these mini-chambers are presented.

关键词： Lab scale storage chamber temperature relative humidity fruit and vegetable quality.

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Modeling and Characterization of Vegetation, Aquatic and Mineral Surfaces Using the Theory of Plausible and Paradoxical Reasoning from Satellite Images: Case of the Toumodi-Yamoussoukro-Tiébissou Zone in V Baoulé(Côte d’Ivoire)

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Open Journal of Applied Sciences 2017年第10期7卷 520-536页

作者： Jean-Claude Okaingni Sié Ouattara Adles Kouassi Wognin J.Vangah Aubin K.Koffi alain clement Laboratory of Signals and Electrical Systems(L2SE) Institut National Polytechnique Houphouet BoignyYamoussoukroCote D’Ivoire Institut National Polytechnique Houphouet Boigny(INPHB) YamoussoukroCote D’Ivoire Ecole Supérieure des Technologies de l’Information et de la Communication(ESATIC) AbidjanCote D’Ivoire Institut Universitaire de Technologie d’Angers(IUT) AngersFrance

In this paper, the theory of plausible and paradoxical reasoning of Dezert- Smarandache (DSmT) is used to take into account the paradoxical charac-ter through the intersections of vegetation, aquatic and mineral surfaces. In order to do this, we developed a classification model of pixels by aggregating information using the DSmT theory based on the PCR5 rule using the ∩NDVI, ∩MNDWI and ∩NDBaI spectral indices obtained from the ASTER satellite images. On the qualitative level, the model produced three simple classes for certain knowledge (E, V, M) and eight composite classes including two union classes characterizing partial ignorance ({E,V}, {M,V}) and six classes of intersection of which three classes of simple intersection (E∩V, M∩V, E∩M) and three classes of composite intersection (E∩{M,V}, M∩{E,V}, V∩{E,M}), which represent paradoxes. This model was validated with an average rate of 93.34% for the well-classified pixels and a compliance rate of the entities in the field of 96.37%. Thus, the model 1 retained provides 84.98% for the simple classes against 15.02% for the composite classes.

关键词： Theory of Plausible and Paradoxical Reasoning PCR5 Rule ASTER Satellite Images NDVI MNDWI NDBaI Modeling Classification

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