Texture aware image segmentation using graph cuts and active contours by Zhou, Hailing, Zheng, Jianmin, Wei, Lei

“…The problem of segmenting a foreground object out from its complex background is of great interest in image processing and computer vision. …”
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Advancements in glioma segmentation: comparing the U-Net and DeconvNet models by Mohammed, AA, Gonzales, RA

“…In this study, we address the challenge of accurately segmenting gliomas from magnetic resonance imaging (MRI) scans, an essential task for treatment planning and prognosis in glioma patients. …”

Anatomically plausible segmentations: explicitly preserving topology through prior deformations by Wyburd, MK, Dinsdale, NK, Jenkinson, M, Namburete, AIL

“…Since the rise of deep learning, new medical segmentation methods have rapidly been proposed with extremely promising results, often reporting marginal improvements on the previous state-of-the-art (SOTA) method. …”

Measurement of brain structures based on statistical and geometrical 3D segmentation by ángel, M, Ballester, G, Zisserman, A, Brady, M

“…In this paper we present a novel method for three-dimensional segmentation and measurement of volumetric data based on the combination of statistical and geometrical information. …”

A study on Stevedoring companies and their operations in Singapore : break bulk shipping segment by Ng, Donovan Chun Hong

“…Considering the importance of stevedores’ contribution to the seamless functioning of our ports, this paper aims to study the development of stevedoring operations in the break bulk shipping segment in Singapore over time and find out the relevance of break bulk stevedores in the rapidly changing environment of break bulk shipping. …”
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Fast and accurate detection of Identical-By-Descent segment sharing in large genomic datasets by Saada, J

“…<p>Identical-By-Descent (IBD) segments are a fundamental measure of ge- netic relatedness and IBD detection is of great interest in many applica- tions, including demographic inference and haplotype-based association. …”

OpenOFM: an open-source implementation of the multi-segment Oxford Foot Model by Dixon, P, Drew, E, McBride, S, Harrington, M, Stebbins, J, Zavatsky, A

“…Evaluation was conducted using the normalised root mean square error (NRMSE) between the inter-segment angles and arch heights of both implementations. …”

'It hurts my heart': Afghan women in London negotiating family relationships and (im)mobility regimes across borders by Ryan, Louise, López, María E., Rasa, Mursal

“…Paying attention to the specificities of spatial contexts and infrastructures in framing opportunities and obstacles to transnational care, we apply the concept of immobility regimes. Beyond a simple bi‐national focus on countries of origin and residence, we explore how the women navigate these regimes, across multiple countries and different visa regimes to arrange in‐person visits with geographically dispersed kin. …”
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Data-driven distributionally robust CVaR portfolio optimization under a regime-switching ambiguity set by Pun, Chi Seng, Wang, Tianyu, Yan, Zhenzhen

“…Methodology/Results: This paper models the nonstationarity by a regime-switching ambiguity set. In particular, we incorporate the time-varying feature of the stochastic environment into the traditional Wasserstein ambiguity set to build our regime-switching ambiguity set. …”
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Optimum transmitter current distribution for dynamic wireless power transfer with segmented array by Jayathurathnage, Prasad Kumara Sampath, Alphones, Arokiaswami, Vilathgamuwa, D. Mahinda, Ong, Andrew

“…The misalignment problem is a major challenge in dynamic wireless power transfer systems with a segmented transmitter (Tx) array. Tx coils farther away from receiver (Rx) experience higher currents as compared to Tx coils nearer to Rx coil leading to higher losses and lower performances. …”
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Dual attention deep learning network for automatic steel surface defect segmentation by Pan, Yue, Zhang, Limao

“…The novel pixel-level detection algorithm called DAN-DeepLabv3+ integrates a dual attention module into the DeepLabv3+ framework in pursue of more precise segmentation results. For one thing, the dual parallel attention module helps to explicitly model rich contextual dependencies over local feature representations in the spatial and channel dimensions. …”
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CRCNet: few-shot segmentation with cross-reference and region–global conditional networks by Liu, Weide, Zhang, Chi, Lin, Guosheng, Liu, Fayao

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Hybrid UNet transformer architecture for ischemic stoke segmentation with MRI and CT datasets by Soh, Wei Kwek, Rajapakse, Jagath Chandana

“…A hybrid UNet and Transformer (HUT) network is introduced to combine the merits of the UNet and Transformer architectures, improving brain lesion segmentation from MRI and CT scans. The HUT overcomes the limitations of conventional approaches by utilizing two parallel stages: one based on UNet and the other on Transformers. …”
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Automated detection and segmentation of vertebral bodies in volumetric abdominal magnetic resonance images by Lin, Dehui.

“…Detection and segmentation of the column of vertebral bodies are intermediate steps required to identify the bone marrow which is considered as the wrongly labeled visceral adipose tissue in the assessment of abdominal obesity. …”
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Automatic segmentation of the choroid in enhanced depth imaging optical coherence tomography images by Tian, Jing, Marziliano, Pina, Baskaran, Mani, Tun, Tin Aung, Aung, Tin

“…This labeling process is tedious and subjective of inter-observer differences, hence, automatic segmentation of the choroid layer is highly desirable. …”
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Rethinking semi-supervised medical image segmentation: a variance-reduction perspective by You, C, Dai, W, Min, Y, Liu, F, Clifton, DA, Zhou, SK, Staib, L, Duncan, JS

“…For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pairs of samples. …”

BiCoS: a bi-level co-segmentation method for image classification by Chai, Y, Lempitsky, V, Zisserman, A

“…The objective of this paper is the unsupervised segmentation of image training sets into foreground and background in order to improve image classification performance. …”

Fostering motivation in TVET students: the role of learner-paced segments and computational thinking in digital video learning by Wan Nor Ashiqin Wan Ali, Wan Ahmad Jaafar Wan Yahaya, Syed Zulkarnain Syed Idrus, Mohd Noorul Fakhri Yaacob

“…This study aims to address this gap by examining how learner-paced predefined segments and CT algorithmic thinking can impact TVET students' perceived motivation. …”
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BLUE OCEAN SHIFT : BEYOND COMPETING - PROVEN STEPS TO INSPIRE CONFIDENCE AND SEIZE NEW GROWTH / by Kim, W. Chan, author 318022, Mauborgne, Renée, author 387551, Hachette Books Group (Online service) 647103

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DEM study of the size-induced segregation dynamics of a ternary-size granular mixture in the rolling-regime rotating drum by Yang, Shiliang, Zhang, Liangqi, Luo, Kun, Chew, Jia Wei

“…In view of the ubiquitous continuous particle size distributions, this study builds on the considerable knowledge gained so far from binary-size mixtures and extends it to a ternary-size mixture to understand the impact of the presence of a third particle size in the three-dimensional rotating drum operating in the rolling flow regime. The discrete element method is employed. The evolution of segregation, the active-passive interface, and the dynamical response of the particle-scale characteristics of the different particle types in the two regions are investigated. …”
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