Segmentation and analysis of cement particles in cement paste with deep learning by Qian, Hanjie, Li, Ye, Yang, Jianfei, Xie, Lihua, Tan, Kang Hai

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Automatic knee segmentation from multi-contrast MR images by Zhang, Kunlei

“…Also, the proposed cartilage segmentation scheme can be applied to the segmentation of other joint structures. …”
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The Japanese economy in crises : a time series segmentation study by Cheong, Siew Ann, Fornia, Robert Paulo, Lee, Gladys Hui Ting, Kok, Jun Liang, Yim, Woei Shyr, Xu, Danny Yuan, Zhang, Yiting

“…The authors performed a comprehensive time series segmentation study on the 36 Nikkei Japanese industry indices from 1 January 1996 to 11 June 2010. …”
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3D-aware instance segmentation and tracking in egocentric videos by Bhalgat, Y, Tschernezki, V, Laina, I, Henriques, JF, Vedaldi, A, Zisserman, A

“…Leveraging our tracked instance segmentations, we showcase downstream applications in 3D object reconstruction and amodal video object segmentation in these egocentric settings.…”

Placing objects in context via inpainting for out-of-distribution segmentation by De Jorge, P, Volpi, R, Dokania, PK, Torr, PHS, Rogez, G

“…When deploying a semantic segmentation model into the real world, it will inevitably encounter semantic classes that were not seen during training. …”

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

“…Initially, we apply our method to the MNIST dataset and subsequently adapt it for use with medical image segmentation datasets, such as retinal fundus images for vessel segmentation and MRI images for heart segmentation. …”

Empowerment or Reinforcement of Gender Regime: Rethinking Social Enterprises’ Intentions and Impact through Gender Lens by Tymosiewicz, Natalia Elizabeth

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Response time characterization of Organic Rankine Cycle evaporators for dynamic regime analysis with fluctuating load by Jiménez-Arreola, Manuel, Wieland, Christoph, Romagnoli, Alessandro

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Uncertainty Quantification in Deep Learning Models of G-Computation for Outcome Prediction under Dynamic Treatment Regimes by Deng, Leon

“…G-Net is a neural network framework that implements g-computation, a causal inference method for making counterfactual predictions and estimating treatment effects under dynamic and time-varying treatment regimes. Two G-Net models have been successfully implemented: one that uses recurrent neural networks (RNNs) as its predictors, and one that uses transformer encoders (G-Transformer). …”
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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. …”

The low overpotential regime of acidic water oxidation part II: trends in metal and oxygen stability numbers by Scott, Soren B., Sørensen, Jakob E., Rao, Reshma R., Moon, Choongman, Kibsgaard, Jakob, Shao-Horn, Yang, Chorkendorff, Ib

“…In this work, we investigate the stability of both the metal atoms and, by quantitative and highly sensitive 18O isotope labelling experiments, the oxygen atoms in a series of RuOx and IrOx electrocatalysts during the OER in the mechanistically interesting low overpotential regime. We show that materials based on RuOx have a higher dissolution rate than the rate of incorporation of labelled oxygen from the catalyst into the O2 evolved (“labelled OER”), while for IrOx-based catalysts the two rates are comparable. …”
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Nanyang venture formula 1: testing and performance evaluation of formula vehicle under FSAE on-track regime by Yip, Seng Han

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The infinite jest: Heri Dono's Punakawan and their metamorphosis throughout Indonesia's new order regime and reformasi era by Syakirah Aqilah Binte Sanusi

“…Ultimately, he privileges the metamorphosis of his punakawan to instil and embody the hopeful empowerment that the Indonesian public fought for in the late 1990s, from the New Order regime until the Reformasi era.…”
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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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