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). …”
Get full text

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

Subjects: Get full text

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. …”
Get full text

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. …”
Get full text
Get full text

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. …”

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. …”
Get full text

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. …”

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text

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). …”
Get full text

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. …”
Get full text

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. …”
Get full text

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.…”
Get full text

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. …”
Get full text
Get full text

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. …”