Bibliografias temáticas / Pore segmentation

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Literatura científica selecionada sobre o tema "Pore segmentation"

Autor: Grafiati

Publicado: 7 de setembro de 2024

Última modificação: 31 de julho de 2025

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Artigos de revistas sobre o assunto "Pore segmentation"

Liu, Lei, Qiaoling Han, Yue Zhao, and Yandong Zhao. "A Novel Method Combining U-Net with LSTM for Three-Dimensional Soil Pore Segmentation Based on Computed Tomography Images." Applied Sciences 14, no. 8 (2024): 3352. http://dx.doi.org/10.3390/app14083352.

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The non-destructive study of soil micromorphology via computed tomography (CT) imaging has yielded significant insights into the three-dimensional configuration of soil pores. Precise pore analysis is contingent on the accurate transformation of CT images into binary image representations. Notably, segmentation of 2D CT images frequently harbors inaccuracies. This paper introduces a novel three-dimensional pore segmentation method, BDULSTM, which integrates U-Net with convolutional long short-term memory (CLSTM) networks to harness sequence data from CT images and enhance the precision of pore

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Fu, Yinkai, Zihan Huang, Yue Zhao, Benye Xi, Yandong Zhao, and Qiaoling Han. "A weakly supervised soil pore segmentation method based on traditional segmentation algorithm." CATENA 249 (February 2025): 108660. https://doi.org/10.1016/j.catena.2024.108660.

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Silva, Italo Francyles Santos da, Alan de Carvalho Araújo, João Dallyson Sousa de Almeida, Anselmo Cardoso de Paiva, Aristófanes Corrêa Silva, and Deane Roehl. "Soil Structure Analysis with Attention: A Deep Deep-Learning-Based Method for 3D Pore Segmentation and Characterization." AgriEngineering 7, no. 2 (2025): 27. https://doi.org/10.3390/agriengineering7020027.

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The pore structure plays a crucial role in soil systems. It affects a range of processes essential for soil ecological functions, such as the transport and retention of water and nutrients, as well as gas exchanges. The mechanical and hydrological characteristics of soil are predominantly determined by the three-dimensional pore pore-space structure. A precise analysis of pore structure can help specialists understand how these shapes impact plant root activity, leading to better cultivation practices. X-ray computed tomography provides detailed information without destroying the sample. Howev

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Berg, Steffen, Nishank Saxena, Majeed Shaik, and Chaitanya Pradhan. "Generation of ground truth images to validate micro-CT image-processing pipelines." Leading Edge 37, no. 6 (2018): 412–20. http://dx.doi.org/10.1190/tle37060412.1.

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Digital rock technology and pore-scale physics have become increasingly relevant topics in a wide range of porous media with important applications in subsurface engineering. This technology relies heavily on images of pore space and pore-level fluid distribution determined by X-ray microcomputed tomography (micro-CT). Digital images of pore space (or pore-scale fluid distribution) are typically obtained as gray-level images that first need to be processed and segmented to obtain the binary images that uniquely represent rock and pore (including fluid phases). This processing step is not trivi

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Yang, Eomzi, Dong Hun Kang, and Tae Sup Yun. "Reliable estimation of hydraulic permeability from 3D X-ray CT images of porous rock." E3S Web of Conferences 205 (2020): 08004. http://dx.doi.org/10.1051/e3sconf/202020508004.

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The hydraulic permeability is a key parameter for simulating the flow-related phenomenon so that its accurate estimation is crucial in both experimental and numerical simulation studies. 3D pore structure can be readily taken by X-ray computed tomography (CT) and it often serves as a flow domain for pore-scale simulation. However, one encounters the challenges in segmenting the authentic pore structure owing to the finite size of image resolution and segmentation methods. Therefore, the loss of structural information in pore space seems unavoidable to result in the unreliable estimation of per

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Li, Mingjiang, Pan Zhang, and Tao Hai. "Pore extraction method of rock thin section based on Attention U-Net." Journal of Physics: Conference Series 2467, no. 1 (2023): 012016. http://dx.doi.org/10.1088/1742-6596/2467/1/012016.

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Abstract This paper proposes a solution to the shortcomings of traditional segmentation methods. The labeling method uses the incomplete labeling method in weakly supervised labeling to simplify labeling and combines transfer learning to initialize the weight of the network in advance. According to the above ideas, an end-to-end deep learning model is trained. The fine rock particles have a greater segmentation impact, and in addition to that, when compared with the popular deep learning semantic segmentation approaches, they also have a significant improvement. The next phase is to continue i

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Idowu, N. A. A., C. Nardi, H. Long, T. Varslot, and P. E. E. Øren. "Effects of Segmentation and Skeletonization Algorithms on Pore Networks and Predicted Multiphase-Transport Properties of Reservoir-Rock Samples." SPE Reservoir Evaluation & Engineering 17, no. 04 (2014): 473–83. http://dx.doi.org/10.2118/166030-pa.

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Summary Networks of large pores connected by narrower throats (pore networks) are essential inputs into network models that are routinely used to predict transport properties from digital rock images. Extracting pore networks from microcomputed-tomography (micro-CT) images of rocks involves a number of steps: filtering, segmentation, skeletonization, and others. Because of the amount of clay and its distribution, the segmentation of micro-CT images is not trivial, and different algorithms exist for achieving this. Similarly, several methods are available for skeletonizing the segmented images

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Lu, An Qun, Shou Zhi Zhang, and Qian Tian. "Matlab Image Processing Technique and Application in Pore Structure Characterization of Hardened Cement Pastes." Advanced Materials Research 785-786 (September 2013): 1374–79. http://dx.doi.org/10.4028/www.scientific.net/amr.785-786.1374.

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Based on Matlab image processing technique and backscattered electron image analysis method, a characterization method is set up to make quantitative analysis on pore structure of hardened cement pastes. Adopt Matlab to acquire images, and carry out gradation and binarization processing for them; use the combination method of local threshold segmentation and histogram segmentation to obtain pore structure characteristics. The results showed that evolution law of pore structure of fly ash cement pastes via Matlab image analysis method is similar to the conclusion obtained through BET and DVS. S

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Liu, Yifei, and Dong-Sheng Jeng. "Pore Structure of Grain-Size Fractal Granular Material." Materials 12, no. 13 (2019): 2053. http://dx.doi.org/10.3390/ma12132053.

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Numerous studies have proven that natural particle-packed granular materials, such as soil and rock, are consistent with the grain-size fractal rule. The majority of existing studies have regarded these materials as ideal fractal structures, while few have viewed them as particle-packed materials to study the pore structure. In this study, theoretical analysis, the discrete element method, and digital image processing were used to explore the general rules of the pore structures of grain-size fractal granular materials. The relationship between the porosity and grain-size fractal dimension was

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Zel, Ivan, Murat Kenessarin, Sergey Kichanov, Kuanysh Nazarov, Maria Bǎlǎșoiu, and Denis Kozlenko. "Pore Segmentation Techniques for Low-Resolution Data: Application to the Neutron Tomography Data of Cement Materials." Journal of Imaging 8, no. 9 (2022): 242. http://dx.doi.org/10.3390/jimaging8090242.

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The development of neutron imaging facilities provides a growing range of applications in different research fields. The significance of the obtained structural information, among others, depends on the reliability of phase segmentation. We focused on the problem of pore segmentation in low-resolution images and tomography data, taking into consideration possible image corruption in the neutron tomography experiment. Two pore segmentation techniques are proposed. They are the binarization of the enhanced contrast data using the global threshold, and the segmentation using the modified watershe

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Teses / dissertações sobre o assunto "Pore segmentation"

Ding, Nan. "3D Modeling of the Lamina Cribrosa in OCT Data." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS148.

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La lame criblée (LC), située dans la tête du nerf optique, joue un rôle crucial dans le diagnostic et l'étude du glaucome, la deuxième cause de cécité. Il s'agit d'un maillage collagénique 3D formé de pores, par lesquels les fibres nerveuses passent pour atteindre le cerveau. L'observation 3D in vivo des pores de la LC est désormais possible grâce aux progrès de l'imagerie de tomographie de cohérence optique (OCT). Dans cette étude, nous visons à réaliser automatiquement la reconstruction 3D des pores à partir de volumes OCT, afin d'étudier le remodelage de la LC au cours du glaucome. La résol

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Wagh, Ameya Yatindra. "A Deep 3D Object Pose Estimation Framework for Robots with RGB-D Sensors." Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-theses/1287.

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The task of object detection and pose estimation has widely been done using template matching techniques. However, these algorithms are sensitive to outliers and occlusions, and have high latency due to their iterative nature. Recent research in computer vision and deep learning has shown great improvements in the robustness of these algorithms. However, one of the major drawbacks of these algorithms is that they are specific to the objects. Moreover, the estimation of pose depends significantly on their RGB image features. As these algorithms are trained on meticulously labeled la

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Seguin, Guillaume. "Analyse des personnes dans les films stéréoscopiques." Thesis, Paris Sciences et Lettres (ComUE), 2016. http://www.theses.fr/2016PSLEE021/document.

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Les humains sont au coeur de nombreux problèmes de vision par ordinateur, tels que les systèmes de surveillance ou les voitures sans pilote. Ils sont également au centre de la plupart des contenus visuels, pouvant amener à des jeux de données très larges pour l’entraînement de modèles et d’algorithmes. Par ailleurs, si les données stéréoscopiques font l’objet d’études depuis longtemps, ce n’est que récemment que les films 3D sont devenus un succès commercial. Dans cette thèse, nous étudions comment exploiter les données additionnelles issues des films 3D pour les tâches d’analyse des personnes

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Madadi, Meysam. "Human segmentation, pose estimation and applications." Doctoral thesis, Universitat Autònoma de Barcelona, 2017. http://hdl.handle.net/10803/457900.

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El análisis automático de seres humanos en fotografías o videos tiene grandes aplicaciones dentro de la visión por computador, incluyendo diagnóstico médico, deportes, entretenimiento, edición de películas y vigilancia, por nombrar sólo algunos. El cuerpo, la cara y la mano son los componentes más estudiados de los seres humanos. El cuerpo tiene muchas variabilidades en la forma y la ropa junto con altos grados de libertad en pose. La cara está compuesta por multitud de músculos, causando muchas deformaciones visibles, diferentes formas, y variabilidad en cabello. La mano es un objeto pequeño,

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Chen, Daniel Chien Yu. "Image segmentation and pose estimation of humans in video." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/66230/1/Daniel_Chen_Thesis.pdf.

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This thesis introduces improved techniques towards automatically estimating the pose of humans from video. It examines a complete workflow to estimating pose, from the segmentation of the raw video stream to extract silhouettes, to using the silhouettes in order to determine the relative orientation of parts of the human body. The proposed segmentation algorithms have improved performance and reduced complexity, while the pose estimation shows superior accuracy during difficult cases of self occlusion.

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Sandhu, Romeil Singh. "Statistical methods for 2D image segmentation and 3D pose estimation." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37245.

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The field of computer vision focuses on the goal of developing techniques to exploit and extract information from underlying data that may represent images or other multidimensional data. In particular, two well-studied problems in computer vision are the fundamental tasks of 2D image segmentation and 3D pose estimation from a 2D scene. In this thesis, we first introduce two novel methodologies that attempt to independently solve 2D image segmentation and 3D pose estimation separately. Then, by leveraging the advantages of certain techniques from each problem, we couple both tasks in a variat

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DELERUE, JEAN FRANCOIS. "Segmentation 3d, application a l'extraction de reseaux de pores et a la caracterisation hydrodynamique des sols." Paris 11, 2001. http://www.theses.fr/2001PA112141.

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Le sol et les materiaux poreux en general, peuvent etre vus comme l'union de deux parties : la partie solide, constituee de differents materiaux (argile, roche etc. ) et la partie vide (espace poral) par ou peuvent s'ecouler des fluides. Une connaissance precise de la structure 3d de la partie vide devrait permettre une meilleure comprehension des phenomenes d'ecoulement, voire meme une prevision des proprietes hydriques de ces materiaux. Les recents progres dans les domaines de l'acquisition d'image rendent de plus en plus abordable l'obtention d'images volumiques de sol, notamment grace a la

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Hewa, Thondilege Akila Sachinthani Pemasiri. "Multimodal Image Correspondence." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/235433/1/Akila%2BHewa%2BThondilege%2BThesis%281%29.pdf.

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Multimodal images are used across many application areas including medical and surveillance. Due to the different characteristics of different imaging modalities, developing image processing algorithms for multimodal images is challenging. This thesis proposes effective solutions for the challenging problem of multimodal semantic correspondence where the connections between similar components across images from different modalities are established. The proposed methods which are based on deep learning techniques have been applied for several applications including epilepsy type classification

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Calzavara, Ivan. "Human pose augmentation for facilitating Violence Detection in videos: a combination of the deep learning methods DensePose and VioNetHuman pose augmentation for facilitating Violence Detection in videos: a combination of the deep learning methods DensePose and VioNet." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-40842.

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In recent years, deep learning, a critical technology in computer vision, has achieved remarkable milestones in many fields, such as image classification and object detection. In particular, it has also been introduced to address the problem of violence detection, which is a big challenge considering the complexity to establish an exact definition for the phenomenon of violence. Thanks to the ever increasing development of new technologies for surveillance, we have nowadays access to an enormous database of videos that can be analyzed to find any abnormal behavior. However, by dealing with suc

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Karabagli, Bilal. "Vérification automatique des montages d'usinage par vision : application à la sécurisation de l'usinage." Phd thesis, Université Toulouse le Mirail - Toulouse II, 2013. http://tel.archives-ouvertes.fr/tel-01018079.

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Le terme "usinage à porte fermée", fréquemment employé par les PME de l'aéronautique et de l'automobile, désigne l'automatisation sécurisée du processus d'usinage des pièces mécaniques. Dans le cadre de notre travail, nous nous focalisons sur la vérification du montage d'usinage, avant de lancer la phase d'usinage proprement dite. Nous proposons une solution sans contact, basée sur la vision monoculaire (une caméra), permettant de reconnaitre automatiquement les éléments du montage (brut à usiner, pions de positionnement, tiges de fixation,etc.), de vérifier que leur implantation réelle (réali

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Livros sobre o assunto "Pore segmentation"

Shiffrar, Maggie. The Aperture Problem. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0076.

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The accurate visual perception of an object’s motion requires the simultaneous integration of motion information arising from that object along with the segmentation of motion information from other objects. When moving objects are seen through apertures, or viewing windows, the resultant illusions highlight some of the challenges that the visual system faces as it balances motion segmentation with motion integration. One example is the barber pole Illusion, in which lines appear to translate orthogonally to their true direction of emotion. Another is the illusory perception of incoherence whe

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Castellani, Claudia, and Marianne Wootton. Crustacea: Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199233267.003.0021.

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This chapter provides an introduction to the Crustacea, one of the most abundant and diverse components of the plankton. Within a single net-haul, the vast diversity within this group, coupled with the large number of species and the morphological similarity both between species and between developmental stages, can often pose a significant identification challenge even to experienced taxonomists. Although all Crustacea originally share a common body plan, their morphology can differ quite markedly due to different degrees of expression of body segmentation patterns and as a result of the loss

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Capítulos de livros sobre o assunto "Pore segmentation"

Jiqun, Zhang, Hu Chungjin, Liu Xin, He Dongmei, and Li Hua. "An Algorithm for Rock Pore Image Segmentation." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46578-3_28.

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Ramon Soria, Pablo, Fouad Sukkar, Wolfram Martens, B. C. Arrue, and Robert Fitch. "Multi-view Probabilistic Segmentation of Pome Fruit with a Low-Cost RGB-D Camera." In ROBOT 2017: Third Iberian Robotics Conference. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70836-2_27.

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Kang, Wenrui, Xu Wang, Jixia Zhang, Xiaoming Hu, and Qin Li. "Two-Way Perceived Color Difference Saliency Algorithm for Image Segmentation of Port Wine Stains." In Communications in Computer and Information Science. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1160-5_5.

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Lu, Siwei, Xiaofang Zhao, Huazhu Liu, and Hongjie Liang. "Semiconductor Material Porosity Segmentation in Flame Retardant Materials SEM Images Using Data Augmentation and Transfer Learning." In Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde240011.

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Non-halogenated flame retardants are becoming the trend in the development of polymer flame retardant materials due to their high flame retardant efficiency and low generation of toxic smoke gases. Non-halogenated flame retardants achieve flame retardancy by forming a dense char layer and generating non-combustible gases, with the micro-porous structure of the char residue being crucial for studying the flame retardant mechanism. This study focuses on the segmentation of pores in scanning electron microscopy (SEM) images of the combustion char layer of non-halogenated flame retardant materials

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Martin, Vincent, and Monique Thonnat. "A Learning Approach for Adaptive Image Segmentation." In Scene Reconstruction Pose Estimation and Tracking. I-Tech Education and Publishing, 2007. http://dx.doi.org/10.5772/4946.

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Vetrivel, S. C., T. P. Saravanan, V. P. Arun, and R. Maheswari. "Innovative Approaches to Market Segmentation Using AI in Emerging Economies." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-7122-0.ch017.

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This chapter explores innovative approaches to market segmentation using artificial intelligence (AI) in emerging economies. Traditional market segmentation techniques often fall short in dynamic and rapidly evolving markets, where diverse consumer behaviors and limited data availability pose significant challenges. AI, with its advanced data processing and pattern recognition capabilities, offers new possibilities for more accurate and actionable market segmentation. In emerging economies, AI-driven segmentation can harness big data from various sources, including social media, mobile usage,

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Han, Dongil. "Real-Time Object Segmentation of the Disparity Map Using Projection-Based Region Merging." In Scene Reconstruction Pose Estimation and Tracking. I-Tech Education and Publishing, 2007. http://dx.doi.org/10.5772/4924.

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Babu, Tina, Rekha R. Nair, Judeson Antony Kovilpaillai, and Mano Antony Shankari. "Generative Adversarial Networks in Object Detection and Segmentation in Remote Sensing Images." In Advances in Geospatial Technologies. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-6900-5.ch006.

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GANs are revolutionizing computer vision, especially in remote sensing through satellite and aerial imagery. These images pose unique challenges: they're complex and contain objects of various sizes, making segmentation difficult. This paper explores how GANs overcome these challenges by generating realistic synthetic data, particularly when labeled data is scarce. We examine specialized variants like cGANs and SegGANs, which excel in land use analysis, urban structure detection, and environmental monitoring. Our approach combines GANs with traditional machine learning to improve object detect

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Engemann, Heiko, Shengzhi Du, Stephan Kallweit, Chuanfang Ning, and Saqib Anwar. "AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation." In Machine Learning and Artificial Intelligence. IOS Press, 2020. http://dx.doi.org/10.3233/faia200770.

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We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object p

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Bhandari, Vedant, Tyson Phillips, and Ross McAree. "Novel Approaches for Point Cloud Analysis with Evidential Methods: A Multifaceted Approach to Object Pose Estimation, Point Cloud Odometry, and Sensor Registration." In Point Cloud Generation and Its Applications [Working Title]. IntechOpen, 2024. http://dx.doi.org/10.5772/intechopen.1004467.

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Autonomous agents must understand their environment to make decisions. Perception systems often interpret point cloud measurements to extract beliefs about their surroundings. A common strategy is to seek beliefs that are least likely to be false, commonly known as cost-based approaches. These metrics have limitations in practical applications, such as in the presence of noisy measurements, dynamic objects, and debris. Modern solutions integrate additional stages such as segmentation to counteract these limitations, thereby increasing the complexity of the algorithms while being internally fla

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Trabalhos de conferências sobre o assunto "Pore segmentation"

He, Chongyu, Zhiwu Xie, Yinlin Chen, and Edward A. Fox. "Nuclear Pore Segmentation in 3D FIB-SEM Images with Dynamic Cyclical Data Augmentation." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825445.

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Li, Haotian, Billal Aslam, and Bicheng Yan. "Enhanced 3D Pore Segmentation and Multi-Model Pore-Scale Simulation by Deep Learning." In SPE Annual Technical Conference and Exhibition. SPE, 2024. http://dx.doi.org/10.2118/220838-ms.

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Abstract Rock permeability characterization is crucial to understanding fluid flow in subsurface geological formations. It contributes to accurately simulating such processes that can address challenges like sustainable hydrocarbon production and geological CO2 sequestration. Recent advancements in deep learning have facilitated efficient permeability prediction in digital rock. However, existing methods often struggle to predict core-scale properties due to limitations in accommodating larger sub-volumes. This study introduces novel approaches integrating deep learning and physics-constrained

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Wang, Hangjun, Guangqun Zhang, Hengnian Qi, and Lingfei Ma. "Multi-objective Optimization on Pore Segmentation." In 2009 Fifth International Conference on Natural Computation. IEEE, 2009. http://dx.doi.org/10.1109/icnc.2009.572.

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Wang, Hangjun, Hengnian Qi, Wenzhu Li, Guangqun Zhang, and Paoping Wang. "A GA-based automatic pore segmentation algorithm." In the first ACM/SIGEVO Summit. ACM Press, 2009. http://dx.doi.org/10.1145/1543834.1543989.

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Qi, Heng-Nian, Feng-Nong Chen, and Ling-Fei Ma. "Pore Feature Segmentation Based on Mathematical Morphology." In IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2007. http://dx.doi.org/10.1109/iecon.2007.4460248.

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Seo, Sunyong, Sangwook Yoo, Semin Kim, Daeun Yoon, and Jongha Lee. "Facial Pore Segmentation Algorithm using Shallow CNN." In 2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2022. http://dx.doi.org/10.1109/cbms55023.2022.00062.

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Malathi, S., S. Uma Maheswari, and C. Meena. "Fingerprint pore extraction based on Marker controlled Watershed Segmentation." In 2nd International Conference on Computer and Automation Engineering (ICCAE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccae.2010.5451426.

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Ma, Zongfang, Ming Duan, Chao Liu, et al. "Better Semantic Segmentation For 3D Printing Concrete Surface Pore Detection." In 2023 42nd Chinese Control Conference (CCC). IEEE, 2023. http://dx.doi.org/10.23919/ccc58697.2023.10239802.

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Joshi, R. M. "Self-Consistent Approximation for Porosity Segmentation." In Indonesian Petroleum Association - 46th Annual Convention & Exhibition 2022. Indonesian Petroleum Association, 2022. http://dx.doi.org/10.29118/ipa22-g-121.

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Carbonate reservoirs have been known to be a major source of hydrocarbons; it is well known that approximately 60% of the oil and 40% of the gas reserves in the world are found in carbonates, yet the understanding of the carbonate reservoir poses a significant challenge in exploration and exploitation. Presence of secondary porosity which differentiates it from clastic reservoirs brings its own set of complexity primarily owing to the poro-perm relationship. Carbonate fields in Bombay offshore (Western offshore of India) are no different. In order to understand the poro-perm complexity of one

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Mohammad, Rafiq Darwis, Deepak Devegowda, Chandra Rai, Mark Curtis, Sanjana Mudduluru, and Sai Kiran Maryada. "Self-Supervised Learning Using Vision Transformer Architecture for Rock Image Segmentation." In SPE Europe Energy Conference and Exhibition. SPE, 2025. https://doi.org/10.2118/225609-ms.

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Abstract The segmentation of microstructural features in Scanning Electron Microscopy (SEM) images of shale samples is critical for petrophysical analyses, including mineralogy quantification, pore network analysis, and pore system identification. However, processing these images efficiently and accurately typically requires supervised deep learning-based methods, such as semantic segmentation algorithms. Semantic segmentation classifies each pixel in an image into a predefined category (e.g., organic material, inorganic material, pore), regardless of the number of times that category appears

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