Готові списки джерел за темами / Mage segmentation

Добірка наукової літератури з теми "Mage segmentation"

Автор: Grafiati
Опубліковано: 30 травня 2022
Оновлено: 31 травня 2022

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Статті в журналах з теми "Mage segmentation"

1

Thayammal, S., and D. Selvathi. "A Review On Segmentation Based I mage Compression Techniques." Journal of Engineering Science and Technology Review 6, no. 3 (June 2013): 134–40. http://dx.doi.org/10.25103/jestr.063.24.

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2

Wang, Hong Ying, and Er Bao Peng. "Research and Design of Walking Mechanism of Robot and the Parameterization Modeling Based on the UG." Applied Mechanics and Materials 454 (October 2013): 82–85. http://dx.doi.org/10.4028/www.scientific.net/amm.454.82.

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Анотація:
The paper introduced image processing technology based on image segmentation about on-line threads images, and describes in detail image processing technology from mage preprocessing, image gmentation, and threaded parameter test. Threaded images of on-line processing parts obtained are introduced as the key technology, Target edge extraction process from the segmented image are also recounted. At last, this article shows a comparison between actual machining parameters of screw thread and the standard parameter , provides the criterion for error compensation.
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3

Godoy, Dalva Maria Alves, and Hugo Cogo-Moreira. "Evidences of Factorial Structure and Precision of Phonemic Awareness Tasks (TCFe)." Paidéia (Ribeirão Preto) 25, no. 62 (December 2015): 363–72. http://dx.doi.org/10.1590/1982-43272562201510.

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AbstractTo assess phonological awareness - a decisive skill for learning to read and write - it is necessary to provide evidence about an instrument construct to present trustworthy parameters for both empirical research and the development of educational intervention and rehabilitation programs. In Brazil, at this moment, there are no studies regarding the internal structure for tests of phonological awareness. This article shows the factorial validity of a test of phonological awareness composed by three sub-tests: two tasks of subtraction of initial phoneme and one of phonemic segmentation. The multidimensional confirmatory factorial analysis was applied to a sample of 176 Brazilian students ( Mage= 9.3 years) from the first to fifth grade of elementary school. Results indicated a well-adjusted model, with items of intermediate difficulty and high factor loadings; thus, this corroboratedthe internal structure and well-designed theoretical conception.
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4

Wan, Guo Chun, Meng Meng Li, He Xu, Wen Hao Kang, Jin Wen Rui, and Mei Song Tong. "XFinger-Net: Pixel-Wise Segmentation Method for Partially Defective Fingerprint Based on Attention Gates and U-Net." Sensors 20, no. 16 (August 10, 2020): 4473. http://dx.doi.org/10.3390/s20164473.

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Анотація:
Partially defective fingerprint image (PDFI) with poor performance poses challenges to the automated fingerprint identification system (AFIS). To improve the quality and the performance rate of PDFI, it is essential to use accurate segmentation. Currently, most fingerprint image segmentations use methods with ridge orientation, ridge frequency, coherence, variance, local gradient, etc. This paper proposes a method of XFinger-Net for segmenting PDFIs. Based on U-Net, XFinger-Net inherits its characteristics. The attention gate with fewer parameters is used to replace the cascaded network, which can suppress uncorrelated regions of PDFIs. Moreover, the XFinger-Net implements a pixel-level segmentation and takes non-blocking fingerprint images as an input to preserve the global characteristics of PDFIs. The XFinger-Net can achieve a very good segmentation effect as demonstrated in the self-made fingerprint segmentation test.
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5

Campbell, N. W., B. T. Thomas, and T. Troscianko. "Automatic Segmentation and Classification of Outdoor Images Using Neural Networks." International Journal of Neural Systems 08, no. 01 (February 1997): 137–44. http://dx.doi.org/10.1142/s0129065797000161.

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The paper describes how neural networks may be used to segment and label objects in images. A self-organising feature map is used for the segmentation phase, and we quantify the quality of the segmentations produced as well as the contribution made by colour and texture features. A multi-layer perceptron is trained to label the regions produced by the segmentation process. It is shown that 91.1% of the image area is correctly classified into one of eleven categories which include cars, houses, fences, roads, vegetation and sky.
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6

Iyer, Aditi, Maria Thor, Ifeanyirochukwu Onochie, Jennifer Hesse, Kaveh Zakeri, Eve LoCastro, Jue Jiang, et al. "Prospectively-validated deep learning model for segmenting swallowing and chewing structures in CT." Physics in Medicine & Biology 67, no. 2 (January 17, 2022): 024001. http://dx.doi.org/10.1088/1361-6560/ac4000.

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Abstract Objective. Delineating swallowing and chewing structures aids in radiotherapy (RT) treatment planning to limit dysphagia, trismus, and speech dysfunction. We aim to develop an accurate and efficient method to automate this process. Approach. CT scans of 242 head and neck (H&N) cancer patients acquired from 2004 to 2009 at our institution were used to develop auto-segmentation models for the masseters, medial pterygoids, larynx, and pharyngeal constrictor muscle using DeepLabV3+. A cascaded framework was used, wherein models were trained sequentially to spatially constrain each structure group based on prior segmentations. Additionally, an ensemble of models, combining contextual information from axial, coronal, and sagittal views was used to improve segmentation accuracy. Prospective evaluation was conducted by measuring the amount of manual editing required in 91 H&N CT scans acquired February-May 2021. Main results. Medians and inter-quartile ranges of Dice similarity coefficients (DSC) computed on the retrospective testing set (N = 24) were 0.87 (0.85–0.89) for the masseters, 0.80 (0.79–0.81) for the medial pterygoids, 0.81 (0.79–0.84) for the larynx, and 0.69 (0.67–0.71) for the constrictor. Auto-segmentations, when compared to two sets of manual segmentations in 10 randomly selected scans, showed better agreement (DSC) with each observer than inter-observer DSC. Prospective analysis showed most manual modifications needed for clinical use were minor, suggesting auto-contouring could increase clinical efficiency. Trained segmentation models are available for research use upon request via https://github.com/cerr/CERR/wiki/Auto-Segmentation-models. Significance. We developed deep learning-based auto-segmentation models for swallowing and chewing structures in CT and demonstrated its potential for use in treatment planning to limit complications post-RT. To the best of our knowledge, this is the only prospectively-validated deep learning-based model for segmenting chewing and swallowing structures in CT. Segmentation models have been made open-source to facilitate reproducibility and multi-institutional research.
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7

Weishaupt, L. L., T. Vuong, A. Thibodeau-Antonacci, A. Garant, K. S. Singh, C. Miller, A. Martin, and S. Enger. "A121 QUANTIFYING INTER-OBSERVER VARIABILITY IN THE SEGMENTATION OF RECTAL TUMORS IN ENDOSCOPY IMAGES AND ITS EFFECTS ON DEEP LEARNING." Journal of the Canadian Association of Gastroenterology 5, Supplement_1 (February 21, 2022): 140–42. http://dx.doi.org/10.1093/jcag/gwab049.120.

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Abstract Background Tumor delineation in endoscopy images is a crucial part of clinical diagnoses and treatment planning for rectal cancer patients. However, it is challenging to detect and adequately determine the size of tumors in these images, especially for inexperienced clinicians. This motivates the need for a standardized, automated segmentation method. While deep learning has proven to be a powerful tool for medical image segmentation, it requires a large quantity of high-quality annotated training data. Since the annotation of endoscopy images is prone to high inter-observer variability, creating a robust unbiased deep learning model for this task is challenging. Aims To quantify the inter-observer variability in the manual segmentation of tumors in endoscopy images of rectal cancer patients and investigate an automated approach using deep learning. Methods Three gastrointestinal physicians and radiation oncologists (G1, G2, and G3) segmented 2833 endoscopy images into tumor and non-tumor regions. The whole image classifications and the pixelwise classifications into tumor and non-tumor were compared to quantify the inter-observer variability. Each manual annotator is from a different institution. Three different deep learning architectures (FCN32, U-Net, and SegNet) were trained on the binary contours created by G2. This naive approach investigates the effectiveness of neglecting any information about the uncertainty associated with the task of tumor delineation. Finally, segmentations from G2 and the deep learning models’ predictions were compared against ground truth labels from G1 and G3, and accuracy, sensitivity, specificity, precision, and F1 scores were computed for images where both segmentations contained tumors. Results The deep-learning segmentation took less than 1 second, while manual segmentation took approximately 10 seconds per image. There was significant inter-observer variability for the whole-image classifications made by the manual annotators (Figure 1A). The segmentation scores achieved by the deep learning models (SegNet F1:0.80±0.08) were comparable to the inter-observer variability for the pixel-wise image classification (Figure 1B). Conclusions The large inter-observer variability observed in this study indicates a need for an automated segmentation tool for tumors in endoscopy images of rectal cancer patients. While deep learning models trained on a single observer’s labels can segment tumors with an accuracy similar to the inter-observer variability, these models do not accurately reflect the intrinsic uncertainty associated with tumor delineation. In our ongoing studies, we investigate training a model with all observers’ contours to reflect the uncertainty associated with the tumor segmentations. Funding Agencies CIHRNSERC
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8

Desser, Dmitriy, Francisca Assunção, Xiaoguang Yan, Victor Alves, Henrique M. Fernandes, and Thomas Hummel. "Automatic Segmentation of the Olfactory Bulb." Brain Sciences 11, no. 9 (August 28, 2021): 1141. http://dx.doi.org/10.3390/brainsci11091141.

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The olfactory bulb (OB) has an essential role in the human olfactory pathway. A change in olfactory function is associated with a change of OB volume. It has been shown to predict the prognosis of olfactory loss and its volume is a biomarker for various neurodegenerative diseases, such as Alzheimer’s disease. Thus far, obtaining an OB volume for research purposes has been performed by manual segmentation alone; a very time-consuming and highly rater-biased process. As such, this process dramatically reduces the ability to produce fair and reliable comparisons between studies, as well as the processing of large datasets. Our study aims to solve this by proposing a novel methodological framework for the unbiased measurement of OB volume. In this paper, we present a fully automated tool that successfully performs such a task, accurately and quickly. In order to develop a stable and versatile algorithm and to train the neural network, we used four datasets consisting of whole-brain T1 and high-resolution T2 MRI scans, as well as the corresponding clinical information of the subject’s smelling ability. One dataset contained data of patients suffering from anosmia or hyposmia (N = 79), and the other three datasets contained data of healthy controls (N = 91). First, the manual segmentation labels of the OBs were created by two experienced raters, independently and blinded. The algorithm consisted of the following four different steps: (1) multimodal data co-registration of whole-brain T1 images and T2 images, (2) template-based localization of OBs, (3) bounding box construction, and lastly, (4) segmentation of the OB using a 3D-U-Net. The results from the automated segmentation algorithm were tested on previously unseen data, achieving a mean dice coefficient (DC) of 0.77 ± 0.05, which is remarkably convergent with the inter-rater DC of 0.79 ± 0.08 estimated for the same cohort. Additionally, the symmetric surface distance (ASSD) was 0.43 ± 0.10. Furthermore, the segmentations produced using our algorithm were manually rated by an independent blinded rater and have reached an equivalent rating score of 5.95 ± 0.87 compared to a rating score of 6.23 ± 0.87 for the first rater’s segmentation and 5.92 ± 0.81 for the second rater’s manual segmentation. Taken together, these results support the success of our tool in producing automatic fast (3–5 min per subject) and reliable segmentations of the OB, with virtually matching accuracy with the current gold standard technique for OB segmentation. In conclusion, we present a newly developed ready-to-use tool that can perform the segmentation of OBs based on multimodal data consisting of T1 whole-brain images and T2 coronal high-resolution images. The accuracy of the segmentations predicted by the algorithm matches the manual segmentations made by two well-experienced raters. This method holds potential for immediate implementation in clinical practice. Furthermore, its ability to perform quick and accurate processing of large datasets may provide a valuable contribution to advancing our knowledge of the olfactory system, in health and disease. Specifically, our framework may integrate the use of olfactory bulb volume (OBV) measurements for the diagnosis and treatment of olfactory loss and improve the prognosis and treatment options of olfactory dysfunctions.
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9

LESTARI, LUXI IKA, and SAINO SAINO. "Analisis Segmentasi Psikografis dan Sensitivitas Harga Konsumen Rumah Makan di Kabupaten Sidoarjo." BISMA (Bisnis dan Manajemen) 3, no. 1 (June 6, 2018): 15. http://dx.doi.org/10.26740/bisma.v3n1.p15-33.

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Анотація:
Now, eat not just tool to fill up a stomach. Eat have been become lifestyle together with period development and culture hase been made of human. So, restaurant necessary to do exactly segmentatiom to develop marketing strategies more exact and specific for their product target on segmen that more specific of poppulation. Psychographic segmentation is kind of segmentation that intercorrelated with individual consumer’s mind, by exploring such factors as value, lifestyle, and cognitive component (Lowe and Worsley,2002) In this research psycographi segmentation just use value that have 18 indicators and lifestyle that have 6 indicators (Lowe and Worsley,2002). Technique that use to taken sample is non probability sampling. To make taken saple easier, researcher use intidental sampling. Data processing technique use validitas and reliabilitas while statistic analysis use factor analysis, cluster analysis, and ANOVA analysis. Psychographic segmentation that connected with price sensitivity have 4 segment are kekanak-kanakan (1225%), alpha sosializer (23,52%), konservatif (14,21%), optimiser (26,47%), self dominance (9,80%), statis (13,72%). There is found price sensitvity different on each segment where segment stick out, alpha sosializer segment is most sensitive, just the opposite segment that have low price sensitivity are optimiser segment and self domonance segment.
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Colebank, Mitchel J., L. Mihaela Paun, M. Umar Qureshi, Naomi Chesler, Dirk Husmeier, Mette S. Olufsen, and Laura Ellwein Fix. "Influence of image segmentation on one-dimensional fluid dynamics predictions in the mouse pulmonary arteries." Journal of The Royal Society Interface 16, no. 159 (October 2, 2019): 20190284. http://dx.doi.org/10.1098/rsif.2019.0284.

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Анотація:
Computational fluid dynamics (CFD) models are emerging tools for assisting in diagnostic assessment of cardiovascular disease. Recent advances in image segmentation have made subject-specific modelling of the cardiovascular system a feasible task, which is particularly important in the case of pulmonary hypertension, requiring a combination of invasive and non-invasive procedures for diagnosis. Uncertainty in image segmentation propagates to CFD model predictions, making the quantification of segmentation-induced uncertainty crucial for subject-specific models. This study quantifies the variability of one-dimensional CFD predictions by propagating the uncertainty of network geometry and connectivity to blood pressure and flow predictions. We analyse multiple segmentations of a single, excised mouse lung using different pre-segmentation parameters. A custom algorithm extracts vessel length, vessel radii and network connectivity for each segmented pulmonary network. Probability density functions are computed for vessel radius and length and then sampled to propagate uncertainties to haemodynamic predictions in a fixed network. In addition, we compute the uncertainty of model predictions to changes in network size and connectivity. Results show that variation in network connectivity is a larger contributor to haemodynamic uncertainty than vessel radius and length.
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Більше джерел

Дисертації з теми "Mage segmentation"

1

Топчієв, Борис Сергійович. "Алгоритмічно-програмний метод колоризації зображень". Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/33832.

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Анотація:
Дана магістерська дисертація присвячена дослідженню та розробці алгоритмічно-програмного методу колоризації зображень за допомогою нейронних мереж. Дана магістерська дисертація включає у себе проведені дослідження проблеми колоризації зображень, власноруч розроблений алгоритмічно-програмний метод для виконання напівавтоматичної колоризації зображень за участю користувача, який вносить власні кольорові підказки. З метою тестування та демонстрації роботи розробленої системи нейронних мереж було створено простий веб-сервіс, який надає можливість користувачу обрати необхідне зображення, за допомогою палітри кольорів внести власні підказки та отримати результат роботи системи. У даній магістерській дисертації проведено детальний аналіз існуючих проблем у роботі з зображеннями, огляд різних алгоритмів для усунення дефектів на зображеннях та запропоновано власний метод для виконання інтерактивної колоризації зображення за участю користувача. Також розроблено простий веб-сервіс, на якому розгорнуто натреновані моделі для їх експлуатації.
This master's dissertation is devoted to the research and development of an algorithmic-software method of coloring images using neural networks. This master's dissertation includes research on the problem of image colorization, self-developed algorithmic-software method for semi-automatic image colorization with the participation of a user who makes their own color prompts. In order to test and demonstrate the work of the developed neural network system, a simple web service was created, which allows the user to select the desired image, use the color palette to enter their own tips and get the result of the system. This master's dissertation provides a detailed analysis of existing problems in working with images, a review of various algorithms for eliminating defects in images and proposed its own method for performing interactive coloring of images with the participation of the user. A simple web service has also been developed, which deploys trained models for their operation.
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2

Lind, Johan. "Make it Meaningful : Semantic Segmentation of Three-Dimensional Urban Scene Models." Thesis, Linköpings universitet, Datorseende, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-143599.

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Semantic segmentation of a scene aims to give meaning to the scene by dividing it into meaningful — semantic — parts. Understanding the scene is of great interest for all kinds of autonomous systems, but manual annotation is simply too time consuming, which is why there is a need for an alternative approach. This thesis investigates the possibility of automatically segmenting 3D-models of urban scenes, such as buildings, into a predetermined set of labels. The approach was to first acquire ground truth data by manually annotating five 3D-models of different urban scenes. The next step was to extract features from the 3D-models and evaluate which ones constitutes a suitable feature space. Finally, three supervised learners were implemented and evaluated: k-Nearest Neighbour (KNN), Support Vector Machine (SVM) and Random Classification Forest (RCF). The classifications were done point-wise, classifying each 3D-point in the dense point cloud belonging to the model being classified. The result showed that the best suitable feature space is not necessarily the one containing all features. The KNN classifier got the highest average accuracy overall models — classifying 42.5% of the 3D points correct. The RCF classifier managed to classify 66.7% points correct in one of the models, but had worse performance for the rest of the models and thus resulting in a lower average accuracy compared to KNN. In general, KNN, SVM, and RCF seemed to have different benefits and drawbacks. KNN is simple and intuitive but by far the slowest classifier when dealing with a large set of training data. SVM and RCF are both fast but difficult to tune as there are more parameters to adjust. Whether the reason for obtaining the relatively low highest accuracy was due to the lack of ground truth training data, unbalanced validation models, or the capacity of the learners, was never investigated due to a limited time span. However, this ought to be investigated in future studies.
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3

Španěl, Michal. "Delaunay-based Vector Segmentation of Volumetric Medical Images." Doctoral thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-261255.

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Image segmentation plays an important role in medical image analysis. Many segmentation algorithms exist. Most of them produce data which are more or less not suitable for further surface extraction and anatomical modeling of human tissues. In this thesis, a novel segmentation technique based on the 3D Delaunay triangulation is proposed. A modified variational tetrahedral meshing approach is used to adapt a tetrahedral mesh to the underlying CT volumetric data, so that image edges are well approximated in the mesh. In order to classify tetrahedra into regions/tissues whose characteristics are similar, three different clustering schemes are presented. Finally, several methods for improving quality of the mesh and its adaptation to the image structure are also discussed.
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4

Ntlapo, Noluthando. "Female-male differentials in earning in South Africa: a comparative socio-demographic approach using data from Labour Force of 2007 and 2011." University of the Western Cape, 2014. http://hdl.handle.net/11394/4327.

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Анотація:
Magister Philosophiae - MPhil
The study examines female-male differentials in earnings and factors associated with them within the labour market of South Africa. Dating back from the end of apartheid in 1994, a few labour policies have been implemented to reduce poverty especially in the area of gender equity and wage discrimination. However, little evidence has been produced to inform on the magnitude of changes in reducing differences and progress achieved so far. Therefore the study attempts to assess and explain the structural changes in female-male differentials in earnings within the labour market. Sparsely conducted studies during the early years of post-apartheid South Africa showed strong racial divide in terms of wage gaps. This proposed study extends this analysis to socio-demographic attributes and also considers a more encompassing notion of earnings. Thus controlling for individual attributes, the overarching issue in this study stems from the following questions: do male workers earn more than their female counterparts within the Labour market? And if it is the case, what are some of the underlying social and demographic variables contributing to this difference? To assess the structural changes in earnings, data utilized for this study are derived from the Labour Force Survey of 2007 and 2011 carried out respectively under Statistics South Africa. Other public records are used to supplement these two sources. In the first step bivariate analysis are carried out to establish patterns and statistical relationships amongst variables selected. Drawing from that, the study makes use of a predictive model to analyse the combined effect of these variables taken together onto the dependent variable. It is expected to observe varying differences in the magnitude of earnings across the selected variables. Differences could be specific to occupation or industrial sector. Temporal variation provides insights about the dynamics of female-male differentials in earnings. From this the study draws some recommendations to guide policy interventions in the labour market.
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5

Andersson, Simon, and Kevin Arnvaller. "Social Media: How to Interact with Millennials and Make Use of Self-Segmentation : A Case Study of Swedish Millennials’ Behavior on Facebook." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-63155.

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Анотація:
Social media are online accommodations where users can interact with other users, which has become a phenomenon that has grown and completely exploded over the past decade. Companies are well aware of this and has invested a large amount of resources in order to establish a better contact with their customers. Companies have several different fields of applications with social media such as gathering information, promotion, communicating with customers and reach out to desired audience effectively. Millennials are the generation who most frequently use social media and also grown up during the phenomenon's development. Previous research has shown that companies have had difficulties in reaching out to the millennial generation. This thesis purpose is to gain a deeper understanding of how companies can use social media to facilitate the segmentation process and effectively reach out to the millennial generation. Therefor two research questions have been established. The two research questions have been answered with assistance from relevant theory and research in the subject area. A case study was applied for the study, where the data was gathered from two focus groups discussing the social media platform Facebook. Each focus group consisted of eight participants within the millennial generation containing basic knowledge in marketing. The study’s result indicates millennials to follow (and thereby self-segment themselves) influential profiles they have a personal interest towards. However, Facebook is not the platform where the millennials follow these profiles. The study also indicates the best way to capture millennials interest on Facebook is through short, humorous videos with an interest capturing beginning. The study’s results also show millennia’s have a low interest in interacting with companies on Facebook.
Sociala medier är onlineplatser där personer kan interagera med varandra. Detta fenomen har vuxit i en accelererande fart under de senaste decenniet och fångat stort intresse hos företag som lägger massiva resurser på att få en bättre kontakt med sina kunder. Företag har åtskilda användningsområden av sociala medier, som till exempel att samla kundinformation, marknadsföra sig, kommunicera med kunder och att nå ut till en önskad målgrupp. Millennials är den generationen som flitigast använder sociala medier och har växt upp under fenomenets utveckling. Tidigare forskning visar att företag har haft svårigheter med att nå ut till millennial generationen. Denna uppsats syfte är därför att ge en djupare förståelse om hur företag kan använda sig av sociala medier för att förenkla segmenteringsprocessen och nå ut till millennial generationen. För att få en djupare förståelse inom område, har vi formulerat två forskningsfrågor. Forskningsfrågorna har i sin tur blivit besvarade med ståndpunkt i relevant teori och forskning inom området. Studien utfördes som en fallstudie, där informationen samlades in från två fokusgrupper som diskuterade Facebook. Vardera fokusgrupp bestod av åtta deltager inom millennial generationen, med grundläggande marknadsförings kunskaper. Studiens resultat indikerar på att millennial generationen följer (och där igenom själv-segmenterar sig själva) inflytande profiler de finner ett personligt intresse för. Dock är Facebook inte den plattform de använder för att följa dessa profiler. Vidare indikerar studien att det bästa sättet att fånga millennial generationens intresse är genom en kort, roligt video, där något intressant händer under de första sekunderna. Studiens resultat visar även att millennial generation inte har något större intresse av att interagera med företag på Facebook.
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6

Eriksson, Malin, and Evelina Lorentzson. "Från retro till metro : Att marknadsföra skönhetsprodukter till män." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-45427.

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Research question: How should cosmetic companies develop marketing strategies for beauty products to appeal to men as a customers? Purpose:The purpose of this paper is to explore how marketing strategies of beauty products aimed  for men should be designed in order to appeal to potential and existing male customers. Furthermore the paper aims to identify strategic proposals that cosmetic companies should apply in creating marketing for men. Method:The case study is based on a qualitative research method with an inductive approach in which the data collected is done through semi-structured interviews and observations. Results: The results show that cosmetics companies should make use of marketing specifically intended for men to appeal as a consumer group. Furthermore, companies should adapt their marketing communications to coincide with men's preferences, interests and characteristics as well as to use market channels for highlighting product ranges intended for men. Limitations: The study of cosmetic companies presents itself on a national level, which means that the conclusion is aimed for the Swedish market and Swedish men. Theoretical and practical contributions: The theoretical contribution of this paper is to overlap the gaps identified in the literature between company and consumer. In order to do so, there must exist a correlation between the marketing mix, segmentation, positioning and target marketing. The practical contributions of this paper is to provide cosmetic companies with proposals of how they should adapt their marketing strategies to appeal to men as a consumer group on the Swedish market.
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Ilten, Paul. "Ansätze für profitables Wachstum von BPO-Dienstleistern." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-175529.

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In dieser Arbeit wird untersucht, wie eine theoriegeleitete Bewertung der Auslagerungseignung von Geschäftsprozessen erfolgen kann und welche Ansatzpunkte für profitables Wachstum von Business Process Outsourcing (BPO)-Anbietern in Deutschland sich aus der Nutzung einer entsprechenden Methodik ableiten lassen. Dazu wird in drei Schritten vorgegangen. In einem ersten Schritt wird ein theoretisch-konzeptionelles Bewertungsmodell zur Bestimmung der Auslagerungseignung von Geschäftsprozessen entwickelt. In einem zweiten Schritt werden Möglichkeiten einer konzeptionellen Übertragung dieses Modells auf Praxisanwendungen geprüft. Im abschließenden dritten Schritt wird gezeigt, wie die Verwendung des in dieser Arbeit entwickelten Bewertungsmodells im Rahmen der Marktbearbeitungsaktivitäten von BPO-Dienstleistern einen Beitrag zum profitablen Wachstum dieser Anbieter leisten kann
In this thesis it is studied how a theory-based assessment of business processes regarding their adequacy for outsourcing can be carried out and what starting points for profitable growth of Business Process Outsourcing (BPO) providers in Germany can result from the application of such a methodology. For this purpose a three step approach is taken. As a first step a theory-based concept of an assessment model to determine the adequacy of outsourcing business processes is developed. As a second step possibilities for transferring the concept of this model to real life applications are examined. In a final third step it is shown how the assessment model developed here can be used as part of the marketing activities of BPO companies to contribute to their profitable growth
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Gamez, Ana Lisa. "The evolution of the male shopper : an approach to new segmentation." Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-12-4743.

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There are many recent studies that indicate an attitudinal change in the male shopper population. Many of these studies indicate dissatisfaction with the majority of current advertising messages because they feel they are not speaking to a male audience. In fact, many male consumers feel that the tone and content of the ad ignores them entirely. This report examines reasons why the male consumer of today is dissatisfied with current advertising messages and where marketers can make revisions. This report 1) studies the gender role shift of the past few decades, how it has impacted the concept of masculinity and what we know about the modern male shopper; 2) evaluates Tuncay’s eight themes of idealized masculinity as they apply to current advertising messages; 3) looks at how a new approach to segmenting the market can improve our understanding; and 4) considers in what way we can apply these findings to marketing practices today.
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Shine, Chen Young, and 陳楊祥. "The Segmentation Research of Male-Leisure-Shoe''s Market in Tai- wan." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/10566589799983769723.

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Yang, Hsiao-Hui, and 楊曉惠. "A Study of Life Style Segmentation of Male Facial Skin Care Products’ Users." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/04905074782361695444.

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碩士
中原大學
商業設計研究所
94
The male skin care market is on the increase, and there are more and more men starting to use male skin care products. So it becomes important to understand what men want and like when they are buying those products. Therefore, the main purpose of this study is to find out what men concern about when they purchase facial skin care products and their consumption behavior. Moreover, this study uses life style as variable to segment male consumers into different consumption groups. The results show that male facial skin care products’ users can be divided into four types. The first type is those who love to use skin care products and have great interest on them. Besides they are also more fashionable. The second type is sporty guys; they show less desire to use skin care products. The third one are the so-called “social animals“, they love to make friends and want to be in the spotlight among a group of people. So they like to use skin care products to make themselves attractive. The final one is those who are shy and conservative, they don’t show strong need of facial skin care products, all they want is cleaning. The four segments show differences in age and occupation. As for other consumption behavior, the four groups also show great diversities. As regards the overall consumers’ behavior, evidence shows that men emphasize on product efficiency, fitness on complexion and reasonable price. Their main products information resources are their friends or relatives, newspapers, publications, advertisements, and public promotion displays. About main buying channels, men tend to buy skin care products in drug stores, supermarkets and department stores.
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Книги з теми "Mage segmentation"

1

Chahal, Gurbaksh. The dream: How I learned the risks and rewards of entrepreneurship and made millions. New York: Palgrave Macmillan, 2009.

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Chahal, Gurbaksh. The Dream: How I Learned the Risks and Rewards of Entrepreneurship and Made Millions. Palgrave Macmillan, 2009.

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Parker, Philip M. The 2007 Report on Hardwood Lumber Made from Purchased Lumber: World Market Segmentation by City. ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007 Report on Wirebound Wood Boxes Made from Lumber: World Market Segmentation by City. ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007 Report on Softwood Lumber Made from Purchased Lumber: World Market Segmentation by City. ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007 Report on Prefinished Wood Moldings Made from Purchased Moldings: World Market Segmentation by City. ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007 Report on Edge-Worked Hardwood Lumber Made from Purchased Lumber: World Market Segmentation by City. ICON Group International, Inc., 2006.

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8

Parker, Philip M. The 2007 Report on Edge-Worked Softwood Lumber Made from Purchased Lumber: World Market Segmentation by City. ICON Group International, Inc., 2006.

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9

Parker, Philip M. The 2007 Report on Wood Moldings Excluding Prefinished Moldings Made from Purchased Moldings: World Market Segmentation by City. ICON Group International, Inc., 2006.

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Parker, Philip M. The 2007 Report on Petroleum Lubricating Oils and Greases Made from Refined Petroleum: World Market Segmentation by City. ICON Group International, Inc., 2006.

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Частини книг з теми "Mage segmentation"

1

Nakata, Toru. "Segmentation and Stillness Make Human Checks Secure." In Advances in Human Error, Reliability, Resilience, and Performance, 99–107. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94391-6_10.

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Cavalcante, André, Fausto Lucena, Allan Kardec Barros, Yoshinori Takeuchi, and Noboru Ohnishi. "Segmentation of Natural and Man-Made Structures by Independent Component Analysis." In Independent Component Analysis and Signal Separation, 483–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00599-2_61.

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Meyr, Herbert. "Customer segmentation, allocation planning and order promising in make-to-stock production." In Supply Chain Planning, 117–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-93775-3_5.

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Terreran, Matteo, Daniele Evangelista, Jacopo Lazzaro, and Alberto Pretto. "Make It Easier: An Empirical Simplification of a Deep 3D Segmentation Network for Human Body Parts." In Lecture Notes in Computer Science, 144–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87156-7_12.

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Karimanzira, Divas, and Helge Renkewitz. "Detection and localization of an underwater docking station in acoustic images using machine learning and generalized fuzzy hough transform." In Machine Learning for Cyber Physical Systems, 23–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62746-4_3.

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AbstractLong underwater operations with autonomous battery charging and data transmission require an Autonomous Underwater Vehicle (AUV) with docking capability, which in turn presume the detection and localization of the docking station. Object detection and localization in sonar images is a very difficult task due to acoustic image problems such as, non-homogeneous resolution, non-uniform intensity, speckle noise, acoustic shadowing, acoustic reverberation and multipath problems. As for detection methods which are invariant to rotations, scale and shifts, the Generalized Fuzzy Hough Transform (GFHT) has proven to be a very powerful tool for arbitrary template detection in a noisy, blurred or even a distorted image, but it is associated with a practical drawback in computation time due to sliding window approach, especially if rotation and scaling invariance is taken into account. In this paper we use the fact that the docking station is made out of aluminum profiles which can easily be isolated using segmentation and classified by a Support Vector Machine (SVM) to enable selective search for the GFHT. After identification of the profile locations, GFHT is applied selectively at these locations for template matching producing the heading and position of the docking station. Further, this paper describes in detail the experiments that validate the methodology.
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Mounter, William, Huda Dawood, and Nashwan Dawood. "The Impact of Data Segmentation in Predicting Monthly Building Energy Use with Support Vector Regression." In Springer Proceedings in Energy, 69–76. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63916-7_9.

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AbstractAdvances in metering technologies and machine learning methods provide both opportunities and challenges for predicting building energy usage in the both the short and long term. However, there are minimal studies on comparing machine learning techniques in predicting building energy usage on their rolling horizon, compared with comparisons based upon a singular forecast range. With the majority of forecasts ranges being within the range of one week, due to the significant increases in error beyond short term building energy prediction. The aim of this paper is to investigate how the accuracy of building energy predictions can be improved for long term predictions, in part of a larger study into which machine learning techniques predict more accuracy within different forecast ranges. In this case study the ‘Clarendon building’ of Teesside University was selected for use in using it’s BMS data (Building Management System) to predict the building’s overall energy usage with Support Vector Regression. Examining how altering what data is used to train the models, impacts their overall accuracy. Such as by segmenting the model by building modes (Active and dormant), or by days of the week (Weekdays and weekends). Of which it was observed that modelling building weekday and weekend energy usage, lead to a reduction of 11% MAPE on average compared with unsegmented predictions.
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Sell, Anna, Pirkko Walden, and Christer Carlsson. "Segmentation Matters." In Mobile and Web Innovations in Systems and Service-Oriented Engineering, 301–17. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2470-2.ch016.

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Despite the penetration of mobile phones in the world the number of mobile services in actual use is – besides voice calls and SMS – rather few. In the study at hand, the authors describe users of mobile phones and mobile services and build the basis for segmentation of the consumer market based on a large random sample of the population. Selecting the correct segmentation base is one of the key steps in any segmentation procedure. The authors carried out life-style segmentation and found five segments – the skillful, the efficient, the trendy, the basic and the social – which offer a systematic description of the mobile consumers, and gives insight on how different users make use of mobile services. The findings are potentially important as mobile service providers do not appear to pay enough attention to consumer segments and the needs of the mobile service users.
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Kashyap, Ramgopal, and Surendra Rahamatkar. "Medical Image Segmentation." In Early Detection of Neurological Disorders Using Machine Learning Systems, 292–321. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8567-1.ch015.

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Today, IoT in therapeutic administrations has ended up being more productive in light of the fact that the correspondence among authorities and patients has been improved with versatile applications. These applications are made by the associations with the objective that the pros can screen the patient's prosperity. If any issue has hopped out at the patient, by then the authority approaches the patient and gives the correct treatment. In this proposition, particular focus is given to infant human administrations, in light of the fact that the greatest fear of gatekeepers is that they would lose their infant kids at whatever point. Therefore, in this part, a business contraption has been recognized which screens the consistent information about the infant's heart rate, oxygen levels, resting position. In case anything happens to the tyke, the information will get to the adaptable application, which has been made by an association and is mechanically available by finishing a representation field test for the kid; the information is recorded and examined.
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Hiziroglu, Abdulkadir. "A Soft Computing Approach to Customer Segmentation." In Intelligent Techniques for Data Analysis in Diverse Settings, 119–46. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0075-9.ch006.

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There are a number of traditional models designed to segment customers, however none of them have the ability to establish non-strict customer segments. One crucial area that can meet this requirement is known as soft computing. Although there have been studies related to the usage of soft computing techniques for segmentation, they are not based on the effective two-stage methodology. The aim of this study is to propose a two-stage segmentation model based on soft computing using the purchasing behaviours of customers in a data mining framework and to make a comparison of the proposed model with a traditional two-stage segmentation model. Segmentation was performed via neuro-fuzzy two stage-clustering approach for a secondary data set, which included more than 300,000 unique customer records, from a UK retail company. The findings indicated that the model provided stronger insights and has greater managerial implications in comparison with the traditional two-stage method with respect to six segmentation effectiveness indicators.
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Hiziroglu, Abdulkadir. "A Soft Computing Approach to Customer Segmentation." In Intelligent Systems, 396–423. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5643-5.ch016.

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There are a number of traditional models designed to segment customers, however none of them have the ability to establish non-strict customer segments. One crucial area that can meet this requirement is known as soft computing. Although there have been studies related to the usage of soft computing techniques for segmentation, they are not based on the effective two-stage methodology. The aim of this study is to propose a two-stage segmentation model based on soft computing using the purchasing behaviours of customers in a data mining framework and to make a comparison of the proposed model with a traditional two-stage segmentation model. Segmentation was performed via neuro-fuzzy two stage-clustering approach for a secondary data set, which included more than 300,000 unique customer records, from a UK retail company. The findings indicated that the model provided stronger insights and has greater managerial implications in comparison with the traditional two-stage method with respect to six segmentation effectiveness indicators.
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Тези доповідей конференцій з теми "Mage segmentation"

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Shum, Judy, Adam Goldhammer, Elena DiMartino, and Ender Finol. "CT Imaging of Abdominal Aortic Aneurysms: Semi-Automatic Vessel Wall Detection and Quantification of Wall Thickness." In ASME 2008 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2008. http://dx.doi.org/10.1115/sbc2008-192638.

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Quantitative measurements of wall thickness in human abdominal aortic aneurysms (AAAs) may provide useful information to predict rupture risk. Our procedure for estimating wall thickness in AAAs includes medical image segmentation and wall thickness detection. Image segmentation requires identifying and segmenting the luminal and outer wall boundaries of the blood vessels and wall thickness can be calculated by using intensity histograms and neural networks. The goal of this study is to develop an image-based, semi-automated method to trace the contours of the vessel wall and measure the wall thickness of the abdominal aorta from in-vivo, contrast-enhanced, CT images. An algorithm for the lumen and inner wall segmentations, and wall thickness detection was developed and tested on 10 ruptured and 10 unruptured AAAs. Reproducibility and repeatability of the algorithm were determined by comparing manual tracings made by two observers to contours made automatically by the algorithm itself. There was a high correspondence between automatic and manual area measurements for the lumen (r = 0.96) and between users (r = 0.98). Based on statistical analyses, the algorithm tends to underestimate the lumen area when compared to both observers.
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Siam, Mennatullah, Naren Doraiswamy, Boris N. Oreshkin, Hengshuai Yao, and Martin Jagersand. "Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/120.

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Significant progress has been made recently in developing few-shot object segmentation methods. Learning is shown to be successful in few-shot segmentation settings, using pixel-level, scribbles and bounding box supervision. This paper takes another approach, i.e., only requiring image-level label for few-shot object segmentation. We propose a novel multi-modal interaction module for few-shot object segmentation that utilizes a co-attention mechanism using both visual and word embedding. Our model using image-level labels achieves 4.8% improvement over previously proposed image-level few-shot object segmentation. It also outperforms state-of-the-art methods that use weak bounding box supervision on PASCAL-5^i. Our results show that few-shot segmentation benefits from utilizing word embeddings, and that we are able to perform few-shot segmentation using stacked joint visual semantic processing with weak image-level labels. We further propose a novel setup, Temporal Object Segmentation for Few-shot Learning (TOSFL) for videos. TOSFL can be used on a variety of public video data such as Youtube-VOS, as demonstrated in both instance-level and category-level TOSFL experiments.
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Ji, Wei, Xi Li, Yueting Zhuang, Omar El Farouk Bourahla, Yixin Ji, Shihao Li, and Jiabao Cui. "Semantic Locality-Aware Deformable Network for Clothing Segmentation." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/106.

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Clothing segmentation is a challenging vision problem typically implemented within a fine-grained semantic segmentation framework. Different from conventional segmentation, clothing segmentation has some domain-specific properties such as texture richness, diverse appearance variations, non-rigid geometry deformations, and small sample learning. To deal with these points, we propose a semantic locality-aware segmentation model, which adaptively attaches an original clothing image with a semantically similar (e.g., appearance or pose) auxiliary exemplar by search. Through considering the interactions of the clothing image and its exemplar, more intrinsic knowledge about the locality manifold structures of clothing images is discovered to make the learning process of small sample problem more stable and tractable. Furthermore, we present a CNN model based on the deformable convolutions to extract the non-rigid geometry-aware features for clothing images. Experimental results demonstrate the effectiveness of the proposed model against the state-of-the-art approaches.
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Jiang, Wanshou, and Junfeng Xie. "TIN based image segmentation for man-made feature extraction." In MIPPR 2005 Image Analysis Techniques, edited by Deren Li and Hongchao Ma. SPIE, 2005. http://dx.doi.org/10.1117/12.655215.

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Pan, Shaoyan, Yang Lei, Tonghe Wang, Jacob Wynne, Justin Roper, Ashesh B. Jani, Pretesh Patel, Jeffrey D. Bradley, Tian Liu, and Xiaofeng Yang. "Male pelvic multi-organ segmentation using V-transformer network." In Biomedical Applications in Molecular, Structural, and Functional Imaging, edited by Barjor S. Gimi and Andrzej Krol. SPIE, 2022. http://dx.doi.org/10.1117/12.2628064.

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Wu, Tong, Bicheng Dai, Shuxin Chen, Yanyun Qu, and Yuan Xie. "Meta Segmentation Network for Ultra-Resolution Medical Images." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/76.

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Despite recent great progress on semantic segmentation, there still exist huge challenges in medical ultra-resolution image segmentation. The methods based on multi-branch structure can make a good balance between computational burdens and segmentation accuracy. However, the fusion structure in these methods require to be designed elaborately to achieve desirable result, which leads to model redundancy. In this paper, we propose Meta Segmentation Network (MSN) to solve this challenging problem. With the help of meta-learning, the fusion module of MSN is quite simple but effective. MSN can fast generate the weights of fusion layers through a simple meta-learner, requiring only a few training samples and epochs to converge. In addition, to avoid learning all branches from scratch, we further introduce a particular weight sharing mechanism to realize a fast knowledge adaptation and share the weights among multiple branches, resulting in the performance improvement and significant parameters reduction. The experimental results on two challenging ultra-resolution medical datasets BACH and ISIC show that MSN achieves the best performance compared with the state-of-the-art approaches.
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Li, Congcong, Lijun Zhang, and Dejian Meng. "A Two-stage Ground Segmentation and Multi-frame Point Clouds Based Road Boundary Extraction Algorithm." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2021-dgt-043.

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Lidar based perceptual system is an important aspect of autonomous driving. In this paper we focus on ground segmentation and road boundary extraction in point cloud. In order to solve the problem that most of the current ground segmentation algorithms can not make full use of the data information, which leads to poor segmentation results on complex roads (such as slopes and undulating roads), this paper presents a two-stage ground segmentation algorithm that combines the Cloth Simulation Filtering (CSF) algorithm and the 2.5D grid map method. In the first stage, CSF is applied to filter out most ground points. Then we project the non-ground points obtained in the first stage to a grid map and judge the attribute of each grid in the map for further segmentation refinement. After ground segmentation, road boundary extraction also plays an indispensable role to obtain drivable area and reduce search space. However, most of road boundary extraction methods focus on single frame data and discard useful historical information. In this paper, the road boundary seed points of the current frame are accumulated from previous multiframe point clouds. After that, the curbs are fitted via the parabola model and RANSAC algorithm. Extensive simulations in Prescan show that the proposed ground segmentation algorithm can adapt to various complex road conditions. Field tests were also conducted to demonstrate the effectiveness of the proposed segmentation method. Our experimental results of road boundary extraction also show that after multiframe accumulation, more detailed information of road boundary can be obtained, resulting in more accurate detection results. In straight part the extraction accuracy of road boundary is more than 96%; in the curve part, the extraction accuracy of road boundary is not as stable as the straight part, but the lowest extraction accuracy is 89.33%, and the average extraction accuracy is 95.64%. Finally, we analyze the influence of localization and attitude angle error on road boundary extraction.
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Zhao, Lujun, Qi Zhang, Peng Wang, and Xiaoyu Liu. "Neural Networks Incorporating Unlabeled and Partially-labeled Data for Cross-domain Chinese Word Segmentation." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/640.

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Most existing Chinese word segmentation (CWS) methods are usually supervised. Hence, large-scale annotated domain-specific datasets are needed for training. In this paper, we seek to address the problem of CWS for the resource-poor domains that lack annotated data. A novel neural network model is proposed to incorporate unlabeled and partially-labeled data. To make use of unlabeled data, we combine a bidirectional LSTM segmentation model with two character-level language models using a gate mechanism. These language models can capture co-occurrence information. To make use of partially-labeled data, we modify the original cross entropy loss function of RNN. Experimental results demonstrate that the method performs well on CWS tasks in a series of domains.
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Liu, Min, and Karthik Ramani. "An edge-based mesh segmentation method for engineering objects." In 2010 International Conference on Mechanic Automation and Control Engineering (MACE). IEEE, 2010. http://dx.doi.org/10.1109/mace.2010.5536720.

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Fan, Haihao, Lei Chen, Chao Feng, Zhe Li, Yuming Zhao, and Su Zhang. "Segmentation of corpus spongiosum from male anterior urethra ultrasound images." In 2017 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2017. http://dx.doi.org/10.1109/icwapr.2017.8076682.

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Звіти організацій з теми "Mage segmentation"

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Patwa, B., P. L. St-Charles, G. Bellefleur, and B. Rousseau. Predictive models for first arrivals on seismic reflection data, Manitoba, New Brunswick, and Ontario. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329758.

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Анотація:
First arrivals are the primary waves picked and analyzed by seismologists to infer properties of the subsurface. Here we try to solve a problem in a small subsection of the seismic processing workflow: first break picking of seismic reflection data. We formulate this problem as an image segmentation task. Data is preprocessed, cleaned from outliers and extrapolated to make the training of deep learning models feasible. We use Fully Convolutional Networks (specifically UNets) to train initial models and explore their performance with losses, layer depths, and the number of classes. We propose to use residual connections to improve each UNet block and residual paths to solve the semantic gap between UNet encoder and decoder which improves the performance of the model. Adding spatial information as an extra channel helped increase the RMSE performance of the first break predictions. Other techniques like data augmentation, multitask loss, and normalization methods, were further explored to evaluate model improvement.
Стилі APA, Harvard, Vancouver, ISO та ін.
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