FAST: An Optimization Framework for Fast Additive Segmentation in Transparent ML by Liu, Brian, Mazumder, Rahul

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Continual semantic segmentation via image and latent space consistency by Wang, Zhichao

“…In this thesis, my continual-learning research process is introduced in detail, including a novel method and two regulators, which contribute to anti-forgetting Result in continual learning in the semantic segmentation area. Firstly a real-time semantic segmentation model called ERFnet is evaluated, then based on this network and Cityscapes dataset, a model-recall method is proposed which could significantly reduce the catastrophic forgetting which happens in the process of continual learning in the semantic segmentation area; inspired by mentors, 2 regulators are also conducted which were expected to further improve performance (one regulator is come up by mentors and another is by myself). …”
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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

“…This thesis is devoted to developing methods for automatic knee segmentation from multi-contrast MR images which provide different contrasts between joint structures and help the separation of different 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

“…This paper introduces a novel approach to instance segmentation and tracking in first-person video that leverages 3D awareness to overcome these obstacles. …”

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

“…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. …”

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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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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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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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

“…Why was wayang a popular visual iconography amongst all sociopolitical/cultural circles in post-independent modern Indonesia, particularly during the Suharto regime? What relationships are explored and fostered between artist-audience in a period where arts censorship was at an all-time high, versus a period where there was more freedom of expression? …”
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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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