Using multiple segmentations to discover objects and their extent in image collections by Russell, BC, Efros, AA, Sivic, J, Freeman, WT, Zisserman, A

“…Given a large dataset of images, we seek to automatically determine the visually similar object and scene classes together with their image segmentation. To achieve this we combine two ideas: (i) that a set of segmented objects can be partitioned into visual object classes using topic discovery models from statistical text analysis; and (ii) that visual object classes can be used to assess the accuracy of a segmentation. …”

Segmentation of magnetic resonance images for assessing neonatal brain maturation by Wang, S

“…We also investigate atlas-based whole brain segmentation that generates the binary mask for the region of interest. …”

DiffuSeg: domain-driven diffusion for medical image segmentation by Zhang, L, Wu, F, Bronik, K, Papiez, BW

“…In recent years, the deployment of supervised machine learning techniques for segmentation tasks has significantly increased. Nonetheless, the annotation process for extensive datasets remains costly, labor-intensive, and error-prone. …”

Semiconductive, one-dimensional, self-assembled nanostructures based on oligopeptides with π-conjugated segments by Sun, Yinghui, Jiang, Lin, Schuermann, Klaus C., Adriaens, Wencke, Zhang, Li, Boey, Freddy Yin Chiang, Cola, Luisa De, Brunsveld, Luc, Chen, Xiaodong

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A new hybrid algorithm for retinal vessels segmentation on fundus images by Dharmawan, Dhimas Arief, Li, Di, Ng, Boon Poh, Rahardja, Susanto

“…Automatic retinal vessels segmentation is an important task in medical applications. …”
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Deep learning approach to cervical segmentation from routine CT images by Duan, Yiming

“…Recently, techniques for 3D medical image segmentation have become increas ingly sophisticated. …”
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Audio segmentation for speech/non-speech detection using wavelet transform by Swe Zin Kalayar Khine.

“…In this project, the noisy audio signal is segmented into speech signal and non-speech signal (that is noise or silence). …”
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Multi-scale space smoothing and segmentation of range data for robot navigation by Tang, Fan

“…This algorithm smoothes range data and segments it at the same time by translating a model based mask over the data. …”
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Novel level set based statistical frameworks for segmentation of MR images by Mahshid Farzinfar

“…In summary, two automated frameworks for segmentation of medical images are proposed. They are the joint curve evolution and the EM-joint shape based algorithms. …”
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Medical image segmentation using random forest and convolutional neural networks by Duan, You

“…This dissertation found that Convolutional Neural Network (CNN) works well in the field of image segmentation. Random Forest (RF) can also obtain good results when processing image segmentation, but it will be affected by the image noise.…”
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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. …”

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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