Machine learning based retinal vessel detection by Li, Hongru

“…Vessel Detection/segmentation based on computer vision and machine learning provides an efficient and economic benefit tool for retinal image analysis. …”
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Fracture identification in well logging images: two-stage adaptive network by Zhang, Wei, Li, Zhipeng, Wu, Tong, Yao, Zhenqiu, Qiu, Ao, Li, Yanjun, Shi, Yibing

“…Automatic fracture identification and segmentation in well logging images is increasingly critical but arduous because of extensive exploration for oil and gas. …”
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Satellite optical and radar image fusion for land cover classification by Zhang, Guobin

“…Following that, different segmentation techniques will be applied to the filtered SAR image, such as Watersheld, Chan-Vese, Superpixel and K-Means segmentation methods. …”
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Self-Supervised Learning across the Spectrum by Shenoy, Jayanth, Zhang, Xingjian Davis, Tao, Bill, Mehrotra, Shlok, Yang, Rem, Zhao, Han, Vasisht, Deepak

“…Satellite image time series (SITS) segmentation is crucial for many applications, like environmental monitoring, land cover mapping, and agricultural crop type classification. …”
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Development of a machine-learning-based detection and tracking algorithm for drones by Er, Hwa Ming

“…However, fewer had tried using semantic segmentation for detection and tracking using drones [1], [2]. …”
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Matching-constrained active contours with affine-invariant shape prior by Yeung, Sai-Kit, Wang, Junyan, Chan, Kap Luk

“…In the object segmentation by active contours, an initial contour provided by user is often required. …”
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Variational model with image denoising fitting term for boundary extraction of breast ultrasound images by Badrulhisam, Nurdina, Ismail, Nurhuda, Jumaat, Abdul Kadir, Maasar, Mohd Azdi, Laham, Mohamed Faris

“…A recent selective variational model, termed the Convex Distance Selective Segmentation (CDSS) model, is effective at segmenting a specific image object. …”
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Robust deep learning methods for accountable contrast-agent-free CMR imaging in clinical applications by Gonzales, RA

“…This approach reduced inter-observer variability and improved the consistency of myocardial segmentation.</p> <br> <p>The fourth goal is to assist the automated segmentation of CMR short-axis slices into the American Heart Association 16-segment model for clinical applications across various CMR modalities. …”

Fast numerical methods for image restoration by Shi, Juan

“…It has been applied to solve the image denoising, segmentation and surface reconstruction problems.…”
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A medical image-based computer-aided diagnosis system for musculoskeletal disease and disorder. by Chuah, Tong Kuan

“…Segmentation is an important and necessary step before features can be quantified to be used in the analysis and classification system. …”
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R-CNN minus R by Lenc, K, Vedaldi, A

“…However, the role of segmentation in CNN detectors remains controversial. …”

Hybrid SLAM and object recognition on an embedded platform by Low, Timothy Zhi Hao

“…The SCALE semantic segmentation is used to perform semantic segmentation on the input provided by the ZED 2 camera. …”
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Variational mesh decomposition by Zhang, Juyong, Zheng, Jianmin, Wu, Chunlin, Cai, Jianfei

“…The problem of decomposing a 3D mesh into meaningful segments (or parts) is of great practical importance in computer graphics. …”
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Weakly supervised learning on road area extraction via classification labels by Liu, Xuanyi

“…Then a gated fusion mechanism aggregates CAM and the segmentation branch’s pixel-level segmentation results to refine an output, supervised by some pseudo labels generated from road centerlines. …”
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Heart cycles using heart sounds by Ng, Jia Long

“…Hence, the first step is to implement and study a reliable method in finding heart sound segmentation. Then, further diagnostic technology can be researched using these segmentation data as it provides an exact location of the heart sound in each heart cycle. …”
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Inhomogeneity correction of magnetic resonance brain images by Chua, Zin Yan

“…In this research, we are focusing on techniques to correct the intensity inhomogeneity by performing a coarse preliminary segmentation on the MR images and then use the segmentation result to estimate the bias field. [3rd Award]…”
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Meta-Learning Frameworks for Imaging Applications / by Sharma, Ashok, 1977-, editor 319639, Sengar, Sandeep Singh, 1985-, editor 656390, Singh, Parveen, 1976-, editor 656391, IGI Global Scientific Publishing (Online service) 655412

“…One critical topic in imaging is image segmentation, and the book explores how a meta-learning-based framework can help identify the best image segmentation algorithm, which would be particularly beneficial in the healthcare domain. …”
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Automated colorization of animated characters by Lin, Jiajun

“…Additionally, image segmentation models, including PSANet and PSPNet, are investigated for possible integration into Segment Matching Models to achieve T-pose Reference-based Prediction. …”
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Toward achieving robust low-level and high-level scene parsing by Shuai, Bing, Ding, Henghui, Liu, Ting, Wang, Gang, Jiang, Xudong

“…In this paper, we address the challenging task of scene segmentation. We first discuss and compare two widely used approaches to retain detailed spatial information from pretrained CNN - "dilation" and "skip". …”
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Semantic mapping for articulated objects by Luar, Shui Song

“…Semantic mapping has advanced greatly since its inception as a research field, to now being able to identify poses and segment objects. As an extension of semantic segmentation problem, there is still an unexplored field of identifying joints of an articulated object within an image. …”
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