Relevant bibliographies by topics / Detection et segmentation des lignes

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Detection et segmentation des lignes'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Detection et segmentation des lignes"

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Lessard, Claude, and Creutzer Mathurin. "L’évolution du corps enseignant québécois : 1960-1986." Revue des sciences de l'éducation 15, no. 1 (2009): 43–71. http://dx.doi.org/10.7202/900617ar.

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Résumé Dans cet article, les auteurs esquissent les grandes lignes d’une problématique de l’évolution du corps enseignant québécois des niveaux primaire et secondaire, de la Révolution tranquille à aujourd’hui. La démarche essentiellement socio-historique aborde à la fois la structuration interne du corps enseignant et ses paramètres d’intégration, de différenciation et de segmentation, et aussi l’évolution de la conception dominante de la fonction enseignante. Une attention est portée à l’Université comme instance de légitimation professionnelle des enseignants. Au plan théorique, les auteurs
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Thirukokaranam, Chandrasekar Krishna Kumar, Kenzo Milleville, and Steven Verstockt. "Species Detection and Segmentation of Multi-specimen Historical Herbaria." Biodiversity Information Science and Standards 5 (September 7, 2021): e74060. https://doi.org/10.3897/biss.5.74060.

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Historically, herbarium specimens have provided users with documented occurrences of plants in specific locations over time. Herbarium collections have therefore been the basis of systematic botany for centuries (Younis et al. 2020). According to the latest summary report based on the data from Index Herbariorum, there are around 3400 active herbaria in the world containing 397 million specimens that are spread across 182 countries (Thiers 2021). Exponential growth in high quality image capturing devices induced by the enormous amount of uncovered collections has further led to rising interest
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Çiftci, Sadettin, and Bahattin Kerem Aydin. "Comment on Lee et al. Accuracy of New Deep Learning Model-Based Segmentation and Key-Point Multi-Detection Method for Ultrasonographic Developmental Dysplasia of the Hip (DDH) Screening. Diagnostics 2021, 11, 1174." Diagnostics 12, no. 7 (2022): 1738. http://dx.doi.org/10.3390/diagnostics12071738.

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We have read the article titled “Accuracy of New Deep Learning Model-Based Segmentation and Key-Point Multi-Detection Method for Ultrasonographic Developmental Dysplasia of the Hip (DDH) Screening” by Lee et al. [...]
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El-shazli, Alaa M. Adel, Sherin M. Youssef, and Marwa Elshennawy. "COMPUTER-AIDED MODEL FOR BREAST CANCER DETECTION IN MAMMOGRAMS." International Journal of Pharmacy and Pharmaceutical Sciences 8, no. 2 (2016): 31. http://dx.doi.org/10.22159/ijpps.2016v8s2.15216.

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<p>The objective of this research was to introduce a new system for automated detection of breast masses in mammography images. The system will be able to discriminate if the image has a mass or not, as well as benign and malignant masses. The new automated ROI segmentation model, where a profiling model integrated with a new iterative growing region scheme has been proposed. The ROI region segmentation is integrated with both statistical and texture feature extraction and selection to discriminate suspected regions effectively. A classifier model is designed using linear fisher classifi
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Nour, Majid, Hakan Öcal, Adi Alhudhaif, and Kemal Polat. "Skin Lesion Segmentation Based on Edge Attention Vnet with Balanced Focal Tversky Loss." Mathematical Problems in Engineering 2022 (June 14, 2022): 1–10. http://dx.doi.org/10.1155/2022/4677044.

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Segmentation of skin lesions from dermoscopic images plays an essential role in the early detection of skin cancer. However, skin lesion segmentation is still challenging due to artifacts such as indistinguishability between skin lesion and normal skin, hair on the skin, and reflections in the obtained dermoscopy images. In this study, an edge attention network (ET-Net) combining edge guidance module (EGM) and weighted aggregation module is added to the 2D volumetric convolutional neural network (Vnet 2D) to maximize the performance of skin lesion segmentation. In addition, the proposed fusion
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Ariouat, Hanane, Youcef Sklab, Marc Pignal, et al. "Extracting Masks from Herbarium Specimen Images Based on Object Detection and Image Segmentation Techniques." Biodiversity Information Science and Standards 7 (September 6, 2023): e112161. https://doi.org/10.3897/biss.7.112161.

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Herbarium specimen scans constitute a valuable source of raw data. Herbarium collections are gaining interest in the scientific community as their exploration can lead to understanding serious threats to biodiversity. Data derived from scanned specimen images can be analyzed to answer important questions such as how plants respond to climate change, how different species respond to biotic and abiotic influences, or what role a species plays within an ecosystem. However, exploiting such large collections is challenging and requires automatic processing. A promising solution lies in the use of c
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Laputin, Fedor A., Ivan V. Sidorov, and Andrey S. Moshkin. "Assessment of ovarian follicular reserve according to ultrasound data based on machine learning methods." Digital Diagnostics 5, no. 1S (2024): 40–42. http://dx.doi.org/10.17816/dd626171.

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BACKGROUND: Ovarian reserve reflects a woman's ability to successfully realize reproductive function. The assessment of ovarian reserve is an urgent task for clinical practice [1] and is important in scientific research. The use of computerized diagnostic image processing methods can accelerate and facilitate the performance of routine tasks in clinical practice. Their use in retrospective data analysis for scientific purposes allows to increase the objectivity of the study and supplement it with auxiliary information [2]. The issue of ovarian localization and follicle segmentation on ultrasou
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Chen, Shuo-Tsung, Tzung-Dau Wang, Wen-Jeng Lee, et al. "Coronary Arteries Segmentation Based on the 3D Discrete Wavelet Transform and 3D Neutrosophic Transform." BioMed Research International 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/798303.

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Purpose. Most applications in the field of medical image processing require precise estimation. To improve the accuracy of segmentation, this study aimed to propose a novel segmentation method for coronary arteries to allow for the automatic and accurate detection of coronary pathologies.Methods. The proposed segmentation method included 2 parts. First, 3D region growing was applied to give the initial segmentation of coronary arteries. Next, the location of vessel information, HHH subband coefficients of the 3D DWT, was detected by the proposed vessel-texture discrimination algorithm. Based o
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Zhong, Johnson. "Analyzing Out-of-Domain Generalization Performance of Pre-Trained Segmentation Models." Network and Communication Technologies 8, no. 1 (2023): 1. http://dx.doi.org/10.5539/nct.v8n1p1.

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Artists illustrate objects to various degrees of complexity. As the amount of detail or the similarity to reality of a depiction decreases, the object tends to be reduced to its simplest, most relevant higher-level features (Harrison, 1981). One of the reasons Deep Neural Networks (DNN) may fail to identify objects in an image is that models are unable to recognize the order of importance of features such as shape, depth, or color within an image, which means even the most minute distortions of pixels within an image that would be imperceptible to humans would greatly impact the performance of
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Jyoti, Kataria Supriya P. Panda. "HybridCSF model for magnetic resonance image based brain tumor segmentation." Indonesian Journal of Electrical Engineering and Computer Science 35, no. 3 (2024): 1845–52. https://doi.org/10.11591/ijeecs.v35.i3.pp1845-1852.

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The human brain comprises a complex interconnection of nerve cells and vital organs, which regulates crucial bodily processes. Although neurons commonly undergo developmental stages, they may occasionally experience abnormalities, leading to abnormal growths known as brain tumors. The objective of brain tumor segmentation is to produce precise boundaries of brain tumor regions. This study extensively analyzes deep learning methods for brain tumor detection, evaluating their effectiveness across diverse datasets. It introduces a hybrid model, which is proposed by the name HybriCSF: hybrid convo
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Dissertations / Theses on the topic "Detection et segmentation des lignes"

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Khairallah, Mahmoud. "Flow-Based Visual-Inertial Odometry for Neuromorphic Vision Sensors." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST117.

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Plutôt que de générer des images de manière constante et synchrone, les capteurs neuromorphiques de vision -également connus sous le nom de caméras événementielles, permettent à chaque pixel de fournir des informations de manière indépendante et asynchrone chaque fois qu'un changement de luminosité est détecté. Par conséquent, les capteurs de vision neuromorphiques n'ont pas les problèmes des caméras conventionnelles telles que les artefacts d'image et le Flou cinétique. De plus, ils peuvent fournir une compression sans perte de donné avec une résolution temporelle et une plage dynamique plus
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Ouwayed, Nazih. "Segmentation en lignes de documents anciens : applications aux documents arabes." Thesis, Nancy 2, 2010. http://www.theses.fr/2010NAN23001/document.

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L'indexation de documents numérisés manuscrits pose le problème de la segmentation en lignes qui, si elle échoue, handicape les étapes suivantes d'extraction et de reconnaissance de mots. Dans les documents arabes anciens, s'ajoute à ce problème, la présence dans les marges, d'annotations souvent composées de lignes obliques. La détection de ces lignes est nécessaire et constitue un défi important pour l'indexation de ces documents. Ainsi, la segmentation visée dans ce travail de thèse concerne l'extraction de lignes multi-orientées. Pour ce problème, la bibliographie ne présente que des techn
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Ouwayed, Nazih. "Segmentation en lignes de documents anciens : applications aux documents arabes." Electronic Thesis or Diss., Nancy 2, 2010. http://www.theses.fr/2010NAN23001.

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L'indexation de documents numérisés manuscrits pose le problème de la segmentation en lignes qui, si elle échoue, handicape les étapes suivantes d'extraction et de reconnaissance de mots. Dans les documents arabes anciens, s'ajoute à ce problème, la présence dans les marges, d'annotations souvent composées de lignes obliques. La détection de ces lignes est nécessaire et constitue un défi important pour l'indexation de ces documents. Ainsi, la segmentation visée dans ce travail de thèse concerne l'extraction de lignes multi-orientées. Pour ce problème, la bibliographie ne présente que des techn
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Cousty, Jean. "Lignes de partage des eaux discrètes : théorie et application à la segmentation d'images cardiaques." Phd thesis, Université de Marne la Vallée, 2007. http://tel.archives-ouvertes.fr/tel-00321885.

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La notion de clivage formalise l'idée d'ensemble frontiére dans un graphe. Fusionner deux régions, comme le requièrent certaines méthodes de segmentation d'images, pose des diffIcultés. Nous introduisons quatre classes de graphes (de fusion) dans lesquels ces diffIcultés sont progressivement supprimées. Nous montrons que l'une de ces classes est celle pour laquelle tout clivage est mince. Nous introduisons une relation d'adjacence, appelée grille de fusion parfaite, dans laquelle deux régions voisines peuvent être fusionnées, en préservant toutes les autres régions.<br /><br />La ligne de part
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Odobez, Jean-Marc. "Estimation, detection et segmentation du mouvement : une approche robuste et markovienne." Rennes 1, 1994. http://www.theses.fr/1994REN10207.

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Cette these traite de la detection et de la localisation d'objets en mouvement dans une sequence d'images acquises par une camera mobile. Nous motivons tout d'abord l'interet du probleme et rappelons diverses methodes existantes proposees pour le resoudre. L'approche que nous avons retenue pour la detection consiste a reconstruire dans un premier temps une sequence d'images, dans laquelle le deplacement apparent dans l'image induit par le mouvement de la camera a ete compense. Pour cela, nous supposons que ce deplacement peut etre decrit par un modele parametrique 2d. Le troisieme chapitre de
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PENG, ANRONG. "Segmentation statistique non supervisee d'images et detection de contours par filtrage." Compiègne, 1992. http://www.theses.fr/1992COMP0512.

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Cette thèse est consacrée à deux catégories de méthodes de la segmentation d'images: la segmentation statistique non supervisée et la détection de contours par filtrage. Les contributions de ce travail reposent sur les études des deux familles de méthodes en soi et sur leur mise en parallèle. Dans la première partie, nous abordons la segmentation Bayesienne non supervisée. Des algorithmes d'estimation préalable à la segmentation contextuelle, tels que EM, ICE, SEM, sont étudiés. Puis ces estimateurs valables dans les champs stationnaires sont adaptés aux champs non stationnaires. En levant l'h
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Migniot, Cyrille. "Segmentation de personnes dans les images et les vidéos." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00677592.

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La segmentation de personnes dans les images et les vidéos est une problématique actuellement au coeur de nombreux travaux. Nous nous intéressons à la segmentation de personnes debout. Pour cela, nous avons mis au point deux méthodes originales : La première est une continuation d'une méthode de détection efficace. On réalise une pré-segmentation en associant aux segments de contour de l'image une valeur de vraisemblance en tant qu'élément d'une silhouette humaine par une combinaison d'histogrammes de gradients orientés (HOG) et de machines à vecteurs de support (SVM) prises à l'échelle des ce
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Sekkal, Rafiq. "Techniques visuelles pour la détection et le suivi d’objets 2D." Thesis, Rennes, INSA, 2014. http://www.theses.fr/2014ISAR0032/document.

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De nos jours, le traitement et l’analyse d’images trouvent leur application dans de nombreux domaines. Dans le cas de la navigation d’un robot mobile (fauteuil roulant) en milieu intérieur, l’extraction de repères visuels et leur suivi constituent une étape importante pour la réalisation de tâches robotiques (localisation, planification, etc.). En particulier, afin de réaliser une tâche de franchissement de portes, il est indispensable de détecter et suivre automatiquement toutes les portes qui existent dans l’environnement. La détection des portes n’est pas une tâche facile : la variation de
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LIAO, QINGMIN. "Detection de contours et segmentation d'images : applications a la teledetection et a la biologie marine." Rennes 1, 1994. http://www.theses.fr/1994REN10183.

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Dans le cadre de cette these, nous avons developpe une methode de detection de contours et une methode de segmentation d'images afin d'aboutir a une meilleure interpretation des images. La premiere methode permet une localisation precise et une detection de contours insensible au bruit. La precision de la localisation a ete obtenue en agrandissant le support de l'image. Pour reduire l'influence du bruit, un indice de confiance du contour tenant compte de la regularite de la surface locale et de certains criteres lies a la perception visuelle a ete etabli. La methode de segmentation basee sur u
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Gresson, Régis. "Segmentation et reconstruction tridimensionnelle du foyer de microcalcifications mammaires." Vandoeuvre-les-Nancy, INPL, 1998. http://www.theses.fr/1998INPL108N.

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Les travaux présentés dans ce mémoire traitent de la segmentation et de la reconstruction tridimensionnelle du foyer de microcalcifications mammaires. Ces travaux sont scindés en deux parties. La première partie a été consacrée à la détermination d'une méthode automatique de détection et de segmentation des microcalcifications. Nous avons évalué et testé les principales méthodes de segmentation répertoriées dans la littérature (le filtrage de chan, la morphologie mathématique en niveaux de gris, la méthode par hystérésis, les méthodes fractales (classique et par les ondelettes) et la technique
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Book chapters on the topic "Detection et segmentation des lignes"

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Tripathy, B. K., and P. V. S. S. R. Chandra Mouli. "Graph Based Segmentation of Digital Images." In Handbook of Research on Computational Intelligence for Engineering, Science, and Business. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2518-1.ch007.

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Image Segmentation is the process of dividing an image into semantically relevant regions. The problem is still an active area due to wide applications in object detection and recognition, image retrieval, image classification, et cetera. The problem is challenging due to its subjective nature. Many researchers addressed this problem by exploring graph theoretic principles. The key idea is the transformation of segmentation problem into graph partitioning problem by representing the image as a graph. The aim of this chapter is to study various graph based segmentation algorithms.
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Trubuil, Alain. "Prospects in Bayesian image analysis." In Highly Structured Stochastic Systems. Oxford University PressOxford, 2003. http://dx.doi.org/10.1093/oso/9780198510550.003.0031.

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Abstract The ideas presented by Hurn et al. offer an excellent review of the impressive work carried out by the statistical community on the Bayesian framework and its application to image analysis. Necessarily the presentation could not be exhaustive and with respect to applications, a consensus has guided the text with modelling illustrated mainly for restoration problems. My aim is to draw attention to detection, labelling, and eventually three-dimensional (3D) segmentation.
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Lakkarasu, Phanish. "Leveraging cloud-native microservices, containers, and serverless architectures for artificial intelligence pipelines." In Designing Scalable and Intelligent Cloud Architectures: An End-to-End Guide to AI Driven Platforms, MLOps Pipelines, and Data Engineering for Digital Transformation. Deep Science Publishing, 2025. https://doi.org/10.70593/978-93-49910-08-9_11.

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AI pipeline automation can be described as orchestrating the machine learning or deep learning life cycle with a software suite. These software suites could be open-source popular tools such as Kube Flow or MLflow, commercial services by platform providers such as AWS SageMaker and Azure ML, or something between which is a solution built on top of orchestration tools such as Apache Airflow or Google Cloud Workflows. These AI pipelines can provide benefits such as organized code, flexible workflows, and easy reproducibility. In machine learning, being able to reproduce your work (and someone do
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Conference papers on the topic "Detection et segmentation des lignes"

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Zhu, Donglin, Lei Li, Rui Guo, and Shifan Zhan. "Fault Detection by Using Instance Segmentation." In International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21249-ms.

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Abstract Fault detection is an important, but time-consuming task in seismic data interpretation. Traditionally, seismic attributes, such as coherency (Marfurt et al., 1998) and curvature (Al-Dossary et al., 2006) are used to detect faults. Recently, machine learning methods, such as convolution neural networks (CNNs) are used to detect faults, by applying various semantic segmentation algorithms to the seismic data (Wu et al., 2019). The most used algorithm is U-Net (Ronneberger et al., 2015), which can accurately and efficiently provide probability maps of faults. However, probabilities of f
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Houshmand, N., K. Esmaeili, and S. Goodfellow. "Enhancing Joint Detection and RQD Estimation in Acoustic Televiewer Imaging Through Automated Instance Segmentation and Deep Learning." In 58th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2024. http://dx.doi.org/10.56952/arma-2024-1047.

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ABSTRACT: Under certain ground conditions, obtaining adequate core specimens for logging can be challenging, leading to low recoveries and poor rock quality designation (RQD). Borehole well logging offers a cost-effective alternative to handling expensive core samples for logging purposes, particularly advantageous for projects constrained by limited resources. To construct a secure subsurface structure, it is vital to identify and detect weak planes. Borehole imaging provides a fast and efficient way to characterize fractures. Acoustic televiewer (ATV) imaging is an effective tool in fracture
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Mehrishal, S., J. Kim, and J. J. Song. "AI-Powered Semi-Automated Trace Detection Techniques on 3D Digital Rock Mass Models." In 58th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2024. http://dx.doi.org/10.56952/arma-2024-0911.

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ABSTRACT: Estimating rock mass structure relies heavily on deciphering trace lines on exposed rock surfaces. Manual detection of traces on 3D digital models can be tedious and time-consuming. This study proposes a novel AI-driven approach to enhance 3D trace surveying, overcoming potential limitations. A custom pixel-wise texture mapper algorithm transforms 3D rock models into virtual 2D images, eliminating access restrictions. DeepLabV3+, a deep-learning network, efficiently detects trace lines within these virtual images. The detected traces are transformed into 3D data through a multi-step
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Wu, Huanyu, Yuan Zou, Qi Zhao, Chi Zhang, and Wei Yang. "Micro-CT Characterization of Lunar Regolith Using Machine Learning-Based Segmentation." In 57th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2023. http://dx.doi.org/10.56952/arma-2023-0281.

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ABSTRACT On 17 December 2020, China's Chang’e-5 mission returned about 1.73 kg of lunar regolith from one of the youngest basalt units in northern Oceanus Procellarum. The mineralogy of the lunar surface regolith provides a wealth of information on its geological history, and the characterization of lunar regolith at high spatial resolution has been a significant goal of lunar exploration. In this study, we combine high-resolution micro-CT imaging and a state-of-the-art machine learning-based image processing approach to assess morphological and physical properties of the lunar regolith sample
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Alamdari, Nasim, Nicholas MacKinnon, Fartash Vasefi, et al. "Effect of Lesion Segmentation in Melanoma Diagnosis for a Mobile Health Application." In 2017 Design of Medical Devices Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dmd2017-3522.

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In 2016, more than 76,380 new melanoma cases were diagnosed and 10,130 people were expected to die from skin cancer in the United States (one death per hour) [1]. A recent study demonstrates that the economic burden of skin cancer treatment is substantial and, in the United States, the cost was increased from $3.6 billion in 2002–2006 to $8.1 billion in 2007–2011 [2]. Monitoring moderate and high-risk patients and identifying melanoma in the earliest stage of disease should save lives and greatly diminish the cost of treatment. In this project, we are focused on detection and monitoring of new
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García Contreras, Erika, and Jorge Lira Chávez. "La percepción remota aplicada al análisis urbano-regional de la ciudad de México empleando imágenes ópticas Terra/Aster y Spot5." In International Conference Virtual City and Territory. Universidad Autónoma de Baja California, 2010. http://dx.doi.org/10.5821/ctv.7622.

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En la actualidad la mayor parte de la población vive en grandes urbes o megalópolis, las cuales son de gran interés para hacer estudios de ciudades empleando métodos de percepción remota. La ciudad de México es una metrópoli con una gran dinámica socio-económica, cultural y de servicios. Esta gran dinámica es una de las principales causas que ocasionan cambios en el uso de suelo urbano. En este trabajo, la investigación se centra en la detección de las estructuras urbanas de la ciudad de México, empleando imágenes ópticas Terra/Aster y Spot-5, mediante el análisis de las siguientes metodología
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Jeong, C., S. Lin, A. Reyes, V. Sharma, and A. S. Wendt. "Enabling Geomechanical Insights from Drilling Data: Automated and Data-Driven Proxy Mechanical Earth Modeling." In 58th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2024. http://dx.doi.org/10.56952/arma-2024-1089.

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ABSTRACT: The energy industry has acknowledged the intricate relationship between mechanical drilling and subsurface geomechanical parameters. However, establishing an accurate connection between these parameters remains technically challenging. Constructing a mechanical earth model (MEM) and utilizing it to predict or monitor mud weight window (MWW) boundaries currently necessitates log data acquisition, processing, and significant expertise in data interpretation, modeling, and correlation identification. To simplify MEM and MWW construction and reduce reliance on log data, an automated and
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