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.…”

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. …”

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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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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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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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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Modeling mass removal and sediment deposition in stormwater ponds using floating treatment islands: a computational approach by Xavier, Manoel L. M., Janzen, Johannes G., Nepf, Heidi

“…Moreover, the FTI configuration exerts a more pronounced influence on mass removal through FTIs than through sediment deposition alone. In cases where both processes occur simultaneously, the presence of FTIs lead to higher mass removal, primarily attributed to the FTIs themselves, particularly in the initial segment. …”
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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. …”