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.…”

Humanising GrabCut: learning to segment humans using the Kinect by Gulshan, V, Lempitsky, V, Zisserman, A

“…To this end we investigate learning to automatically segment humans from cluttered images (without depth information) given a bounding box. …”

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. …”

Attention and positive sentiments towards carbon dioxide removal have grown on social media over the past decade by Repke, T, Müller-Hansen, F, Cox, E, Minx, JC

“…Here, we analyse attention and sentiments towards ten CDR methods using Twitter data from 2010 to 2022. …”

Attention and positive sentiments towards carbon dioxide removal have grown on social media over the past decade by Repke, T, Müller-Hansen, F, Minx, JC, Cox, E

“…Here, we analyse attention and sentiments towards ten CDR methods using Twitter data from 2010 to 2022. …”

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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Unconventional physical activity promotion : exploring the effectiveness of DDP yoga through sentiment analysis on Twitter by Lim, Ryan

“…Tweets that mentioned DDPY were collected, and 13,069 tweets from 4,343 unique users were analysed through topic modelling and sentiment analysis. Results indicated particularly positive sentiments among Twitter users and many tweets were focused on providing support and encouragement for the DDPY community. …”
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Public opinion trend analysis on nuclear energy via aspect-based sentiment analysis methods by Huang, Fan

“…The subjective emotions and sentiment information within textual data present people's thoughts and attitudes towards specific themes. …”
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A scheme of pairwise feature combinations to improve sentiment classification using book review dataset by Abubakar, Haisal Dauda, Huspi, Sharin Hazlin, Mahmood Umar, Mahmood Umar

“…Sentiment Analysis is a Natural Language Processing (NLP) domain related to the identification or extraction of user sentiments or opinions from written language. …”
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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

“…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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